1. Introduction The history of scientific computing in India dates back to the 1950’s, right from the time India started its research activities as an independent country. The growth of computing as a discipline in India has been somewhat slower in the first 3 – 4 decades and had its ups-down. Dependent on the western counties for the technology and the prohibitively expensive cost of computing systems has been the major factor in this slow growth. Nonetheless, the growth was steady and matured to the right level where the researchers can not only exploit the new technology but also innovate and enable them. A clear evidence of this is the dramatic growth in high performance computing witnessed in last 15 – 20 years in India. From the state of longing for a single mainframe high performance system for the entire country, the nation has moved to state where it is capable of building high performance computing systems (with both off-the-shelf components exported from other countries and indigeneously developed components, specifically for network subsystem). The expertise to effectively use the high performance computing systems has been growing steadily since the days of induction of parallel computing systems in India in the early 1990s. The Indian government has been instrumental in enabling this change. Starting from the early initiative which encouraged the design of the TIFRAC system (see discussion on this in Section XX), to the founding of the Centre for the Development of Advance Computing for the design of parallel computer systems, to the most recent Grid Garuda initiative, the government has significantly funded major research initiatives in the high performance computing system. The support given by the government were fully supplemented by the efforts of various research organizations and their researchers to make sure they lead to growth and competence in the high performance computing area. Today, researchers in India work on various aspects of high performance computing --- system architecture, performance evaluation, software system, and applications --- to advance the frontiers of science and engineering through high performance computing.. In this report we present the facilities available at some of the organizations/institutions and their research efforts. A comprehensive report on either of these would be near impossible and we do not attempt it here. Instead, we try to present a flavor of both these in the report and possible future directions the HPC research in India might take. In the next section, we give a brief history of HPC in India. We then list and give a brief profile of the HPC centers we have considered and their HPC facilities. In addition to the isolated HPC centers, the Indian Grid initiative called Garuda has established a federation of multiple HPC facilities located at distributed sites to form a grid system. We describe the Garuda grid framework in detail. We then describe the applications that are executed in these HPC centers, with focus on three major application areas, namely, climate modeling, bioinformatics and computational physics. We then present the system software development work for HPC systems. The HPC capability of India is tracked by a project called Top Supercomputers-India. This project lists the top powerful supercomputers in India twice a year and is the Indian equivalent of the Top500 project that lists the 500 powerful supercomputers in the world. We also describe the project and its current status. The HPC activities in India are also nurtured by some major conferences and workshops that have specific focus of HPC in India. We also give a description of these conferences, and events. Finally, we present the future roadmap of HPC in India. 2. History of High Performance Computing in India 2.1 Computing Facilities India’s research in using computing systems for scientific calculation started way back in the 1960’s. Indian researchers used some of early mainframes available at select institutions in the country. The IBM 1620 and IBM 7044 (at the Indian Institute of Technology, Kanpur), the IBM 1401 (at the Indian Statistical Institute, Calcutta), the CDC 3600 (at the Tata Institute of Fundamental Research, Bombay), and the IBM 360/44 (at the Indian Institute of Science, Bangalore) were some of the early mainframe systems. Subsequently other mainframes such as the IBM 370/165 (at the Indian Institute of Technology, Madras), the DEC 1077 (at the Tata Institute of Fundamental Research, Bombay) and the DEC 1090 systems (at the Indian Institute of Science, Bangalore and the Indian Institute of Technology, Kanpur) were installed and used extensively by researchers in 1970’s. Computing applications were mainly in the areas of finite element analysis, computational fluid dynamics, protein structure, power system analysis, and structural chemistry and solid state physics. Simultaneously research and graduate programs in computer science started in India in mid 1960’s. Research groups grew at the Tata Institute of Fundamental Research, Bombay, the Indian Institute of Science, Bangalore, the five Indian Institutes of Technology, Indian Statistical Institute, Calcutta, Jadavpur University, and the Birla Institute of Technology and Science, for example. Early focus was on numerical computing, theory of algorithms, complexity, program verification and formal techniques for programming, systems software and programming, and artificial intelligence. Research in high performance computing started in India in the mid 1980’s. Several academic institutions /research organizations aspired to acquire supercomputing systems in order to meet the demands of their computational scientists/engineers. At the Indian Institute of Science, Bangalore, an initiative to set up a national supercomputing facility was started by the Department of Electronics and Ministry of Human Resource Development, Government of India in mid 1980’s. This fructified as the Supercomputer Education and Research Centre (SERC) which hosts a number of high performance computing systems in the country. Disheartened by delays in procuring a Cray XMP system, SERC hosted a Cyber 992 system and a VAX 8800 system in the late 1980’s and early 1990’s. Also, SERC set up one of the first workstation farm of IBM headless workstations connected by a network. SERC also deployed a PARAM 8000 machine, indigenously developed in India by the Centre for Development of Advanced Computing (C-DAC). By 1993/94, SERC hosted a variety of distributed high performance computing systems such as IBM’s 32-node Scalable Parallel (SP) system, SGI’s 6- processor Power Challenge system as well as an 8-processor DEC-8400 system in addition to a large number of IBM and Sun workstations. Around the same time, a national initiative in supercomputing in the form of a time bound mission to design, develop, and deliver a supercomputer in the Gigaflop range was launched. This fueled HPC systems research in research organizations (outside an academic institution). Organizations such as Centre for Development of Advanced Computing (C-DAC), Centre for the Develop of Telematics (C-DoT), Bhaba Atomic Research Centre (BARC), Advanced Numerical Research Group (ANURAG), and National Aerospace Laboratories (NAL) initiated several complementary projects to develop high performance computing systems. While C-DAC came us with the first indigenous supercomputing system, called PARAM 8000 series, which used Inmos 800 and 805 Transputers to achieve a theoretic peak performance of 1 Gigaflop. The sustained speedup achieved was 100-200 MegaFLOPS. Other research organizations joined the race with parallel systems ranging from 8-nodes to 64-nodes have been designed and developed independently. More details on the history of parallel computing can be found in [KahanerReport96]. India’s first Top500 system came from CDAC, Bangalore, in June 2003 with the Param Padma supercomputer. It featured in the Top500 list at rank number 169. It is the first supercomputer to find place in the Top500 list which is indigenously designed, developed and commissioned in India. It used a cluster of 62 4-way, IBM pSeries P630 nodes interconnected through a high performance System Area Network, PARAMNet-II, designed and developed by C-DAC and achieved a sustained performance of 532 GigaFLOPS. Another supercomputing development at an academic environment was carried out at the Institute of Mathematical Sciences, Chennai (IMSC). This linux cluster, named Kabru, with 144 nodes (Intel Dual Xeon 2.4 GHz) interconnected by Dolphin 3D SCI network. The cluster achieved a sustained performance of 959 GigaFLOPS and was ranked 264 in the June 2004 Top500 list. This was the first Top500 system from an academic institution in India. The system was built to perform large scale numerical simulations in the area of Lattice Gauge Theory. Eka (the Sanskrit name for number one), developed by Computational Research Laboratories (CRL), Pune, with technical assistance and hardware provided by Hewlett-Packard, was the first to break into the top 10 ranking in the Nov. 2007 Top500 list. This system has 1780 computing nodes (3560 Intel QuadCore Xeon 3GHz) interconnected by a CLOS network with Infiniband interconnect technologies. It achieved a sustained performance of 132.8 TeraFLOPS and was ranked 4 in the Top500 list (Nov. 2007). In the last 5 years a number of (10-15) high performance computing systems have been developed/acquired with performance ranging from 4 TeraFLOPS – 20 TeraFLOPS at various academic institutes (mostly clusters). More importantly there are a large number of smaller clusters with performance ranging from 500 GigaFLOPS to 1 TeraFLOPS which are used for developing high performance application in various disciplines in science and engineering. 2.2 Computer Systems Research in India India’s first effort in building a large digital computer started way back in 1954, when a team of scientists at the Tata Institute of Fundamental Research, Bombay, embarked on the design of TIFRAC (TIFR Automatic Calculator). It was fashioned on the general principles enunciated in the classic von Neumann report. The basic components of this machine were the arithmetic unit, the memory unit, the input-output unit, and of course, the control unit. TIFRAC used an innovative carry bypass adder, textual and graphical output on a visual display on a CRT screen, and 1024 words of the then relatively new ferrite core memory. When completed in 1960, TIFRAC had 2700 vacuum tubes, 1700 germanium diodes and consumed a total power of 18 Kilowatt. [TIFR-AALec]. TIFRAC also resulted in the first attempts at system programming in India. In 1966, the country took a quantum leap as the second-generation computer, first transistor-driven computer, was indigenously developed. The computer was the product of a joint venture between the scientists of the Indian Statistical Institute, Calcutta, and those of Jadavpur university and was fondly nicknamed `ISIJU'. Academic research in mid 1980s focused on Fifth Generation Systems which resulted in several research efforts on dataflow computing systems. Research work on Knowledge Based Computer Systems (KBCS) project, funded by Department of Electronics with the assistance of the United Nations Development Program (UNDP), focused on parallel processing, including parallel processing machines, logic programming environments, and the engineering of parallel AI workstations. The national initiative to design, develop, and deliver a supercomputer and the founding of the C-DAC in the late 1980’s, triggered a series of research efforts in building supercomputing systems. Other research organizations such as C-DoT, BARC, ANURAG, and NAL were involved in the design of parallel computer systems and associated software. These efforts resulted in a series of parallel systems during the 1990s. C-DAC’s sustained efforts fructified as a series of PARAM systems (PARAM 10000, PARAM Padma, and more recently the PARAM Yuva). In addition to development of these system, CDAC als developed the software stack for the PARAM systems and developed the PARAMNet-II interconnection network, which is a significant HPC system design and development work in India. 3. High Performance Centers and Facilities The Computational and Research Lab (CRL), Pune, a wholly owned subsidiary of Tata Sons Limited (a group holding company), has been specially set up to achieve global leadership in the field of High Performance Computing (HPC). CRL’s interests include computer system architecture, parallel system design, parallel systems software, hardware design and interconnection networks, parallel scientific, engineering, digital media, communication and business analytics software libraries and applications. CRL hosts the fastest the HPC system in India, , called EKA, currently ranked at No. 13 (Nov. 2008 list) with a sustained performance of 132.8 TeraFLOPS and a peak performance of 172.6 TeraFLOPS. It uses infiniband interconnect technology and supports a parallel cluster file system for data storage. It was the fastest system in Asia and 4th fastest system in the November 2007 Top500 list. The system is extensively used for various Computational Fluid Dynamic applications, graphics animation, and weather and climate modeling applications. The HPC system research focus of CRL has been on the development of Interconnect systems based on Infiniband hardware and the development of FPGA based accelerators for various integer applications. CRL is also working on system level network topology simulation tools for study of future large system behavior. EKA Supercomputer in CRL, Pune The Centre for Development of Advanced Computing (C-DAC), established in March 1988, as a Scientific Society of the Department of Information Technology (formerly, Dept. of Electronics), Ministry of Communications and Information Technology (formerly, Ministry of Information Technology), Government of India, is primarily an R & D institution involved in the design, development and deployment of advanced Information Technology (IT) based solutions. CDAC is engaged in the design, development and deployment of High Performance Computing (HPC) Systems and Solutions. Over the past two decades, C-DAC has delivered a series of PARAM supercomputers and has built national capabilities to make use of supercomputing technologies for human enrichment. The National Param Supercomputer Facility at Pune and TeraScale Supercomputer Facility at Bangalore are CDAC’s primary HPC centers. CDAC’s Param Padma in 2003 was one of the first Indian systems to enter Top 500, a periodically updated list that maintains the list of top supercomputers of the world. PARAM Yuva is a latest addition to the PARAM series. This system with 288 nodes, sustained performance of 37.80 TFs and peak performance of 54.01 TFs has ranked 68th in the coveted list of Top500 supercomputers of the world and is the 2nd powerful system in India according to TopSupercomputers-India. Para Yuva uses several indigenously designed system components including ParamNet System Area Network, accelerator cards, application and system software suite. Param YUVA in CDAC, Pune The C-DAC Bangalore, houses the Param Padma TeraFLOP cluster, the first Top500 system from India, which is a 248 CPU cluster with IBM Power 4 processors. As a part of the Grid initiative, the centre augmented the Param Padma with a TeraFLOP of computing power with an additional 168 cores of IBM Power 5 processors. More recently the centre has added a 4 TeraFLOP (peak performance) 320-core Intel Xeon based cluster to its computational facility. (RG: I have included some words about Param Padma in the previous para. There is some redundancy here). Param PADMA in CDAC, Bangalore The Center for Modeling, Simulation and Design (CMSD), University of Hyderabad, is an established approved by Union Grants Commission (UGC), and is supported by Department of Science and Technology (DST) under its FIST (Fund for Improvement of S&T Infrastructure in Higher Educational Institutions) programme. CMSD is a state-of- the-art High Performance Computing (HPC) center and focuses on computer based simulations of scientific applications and realizes the importance of scientific research, based on modeling, simulation and design. The Center for Modeling, Simulation and Design (CMSD), University of Hyderabad, has a 2.0 TeraFlop consisting of 6 SMP systems and 4 Tera Bytes of storage, and a CDAC Param cluster with 16 nodes. Indian National Centre for Ocean Information Services (INCOIS) is an autonomous organization under Ministry of Earth Sciences (MoES), Govt. of India. The mission of INCOIS is to provide information and advisory services to society, industry, government agencies and scientific community through sustained ocean observations and constant improvements through systematic and focussed research. INCOIS is involved in various activities including implementing potential fishing zone advisories, developing and maintaining Argo profiling floats for measurement of temperature and salinity through the upper 2000 metres of the open Indian Ocean in real time, and R&D in area of ocean- atmosphere modeling focusing on the ocean predictability and climate variability. It is also the organization responsible for providing early warning for tsunami and storm surges. INCOIS was designated as the National Oceanographic Data Centre under the International Oceanographic Data Exchange programme of the Intergovernmental Oceanographic Commission of UNESCO. Indian National Centre for Ocean Information Services (INCOIS) possesses a 80 processor SGI cluster and a 100 TeraByte storage system to meet its specific requirements of running coastal, regional and global/regional ocean models in operational, data assimilation and other future computational requirements for handling large amounts of data. The Tata Institute of Fundamental Research (TIFR), is an autonomous Institute established in 1945 under the umbrella of the Department of Atomic Energy of the Government of India. TIFR does basic research in physics, chemistry, biology, mathematics and computer science. TIFR has campuses in Mumbai (Bombay), Pune and Bangalore and research facilities in various other places in India. TIFR was one of the few academic institutions to host a computer system in the early 1960s. TIFR is also known for its pioneering work in developing the first indigenous computing system using vacuum tubes, called TIFRAC. The computer centre at TIFR, Bombay, presently hosts a CRAY X1 (acquired in 2004) and a Blue Gene P (acquired later in 2008). The Cray has 16 vector processors, each 12.8 GFLOPS (total of nearly 200 GigaFLOPS). The BlueGene/P has 1024 processors (4096 cores) which achieved a sustained performance of 11.32 TeraFLOPS on HP Linpack code. Major HPC applications include Quantum chromodynamics, quantum field theory, condensed matter and statistical physics. Supercomputing Facility for Bioinformatics & Computational Biology (SCFBIO) is a HPC center at Indian Institute of Technology (IIT) Delhi. Its mission is to develop highly efficient algorithms for genome analysis, protein structure prediction and active site directed drug design. The facility is committed towards providing bioinformatics and computational biology tools and software freely accessible to bioinformatics community. SCFBIO possesses a 104 core AMD Opteron cluster and a 70 core Sun Fire Ultra Sparc III cluster with a 4 TeraByte SAN storage system and a combined performance of 0.7 TeraFlops. It will soon install a 600 core AMD Opteron cluster with 12 TeraBytes of Direct Attached Storage (DAS) for storing the data, and a combined performance of 4 TeraFlops. Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) is located in the north of Bangalore. The Centre for Computational Materials Science (CCMS) is a unit of JNCASR. CCMS, JNCASR, has a 512 core HP Prolian cluster with 32 TeraByte aggregate storage capacity. The cluster is ranked 8th in the latest list of Top Supercomputers-India. The National Centre for Biological Sciences (NCBS), Bangalore, is part of the Tata Institute of Fundamental Research and is located in Bangalore. The mandate of NCBS is basic research in the frontier areas of biology. The research interests of the faculty are in four broad areas ranging from the study of single molecules to systems biology. NCBS possesses 3 AMD Opteron based clusters with a total of 420 cores. Supercomputer Education and Research Centre (SERC) is a department in Indian Institute of Science, Bangalore. It is conceived of as a functionally distributed supercomputing environment, housing leading-edge computing systems, with sophisticated software packages, and connected by a powerful high-speed fibre-optic network. The center possesses multiple high performance clusters including a 8192-core IBM BlueGene/L cluster, 256-core IBM Power5 based Linux cluster, three 32-core IBM Power4+ processor Regatta systems, a 32-core Intel Itanium2 SGI Altix 3700 system, two 16-core Intel Itanium2 SGI Altix 350 system, a 16-core IBM RS/6000 SP3, and a six 4-core COMPAQ AlphaServer ES40 with a total of 8648 cores and a combined capacity of about 25 TFlops. Its IBM BleGene/L system is the 3rd powerful system in India according to Top Supercomputers-India and is ranked 213th in the latest Top500 list. IBM BlueGene/L in SERC, IISc, Bangalore [RG: You may want to move SERC up the order] While we have covered a few major computational facilities in India, the list is by no means comprehensive. We observe that both the number of the HPC facilities and the performance capabilities has been on the increase in the last 5 years. The advent of multicore architectures has enabled quite a few HPC systems in India which have more than 128 cores and a peak performance in excess of 1 TeraFLOP. We anticipate that the number of such systems at present to be at least 50 or more. These are predominantly used for various high performance applications. Not surprisingly, only a few (less than 5) of these systems are used for HPC system research. 4. Garuda – Indian Grid Initiative The National Grid Computing Initiative GARUDA is a collaboration of science researchers and experimenters on a nation wide grid of computational nodes, mass storage and scientific instruments that aims to provide the technological advances required to enable data and compute intensive science for the 21st century. A computational grid is an aggregation of heterogeneous and geographically distributed resources such as computing, storage and special equipments. The aim of the grid is to dynamically share resources to facilitate optimal utilization. Building a commanding position in Grid computing is crucial for India. Allowing anyone, anywhere, anytime to access supercomputer level processing power and knowledge resources, grids will underpin progress in Indian science, engineering and business. The Department of Information Technology (DIT), Government of India has funded the Centre for Development of Advanced Computing (C-DAC) to deploy the nation-wide computational grid GARUDA. To achieve its objective, GARUDA brings together a critical mass of well-established researchers, from 45† research laboratories and academic institutions of India, who have constructed an ambitious program of activities. In Proof of Concept (PoC) phase of GARUDA, 45 R&D and academic institutes from 17 cities across the country were connected with an aim to bring “Grid” networked computing to research labs and industry. From April 2008 the Foundation Phase of GARUDA is in progress with an aim to include more users’ applications, providing Service Oriented architecture, improving network stability and upgrading grid resources. GARUDA – The Indian National Grid Computing Imitative Currently GARUDA has aggregated HPC resources from CDAC centers and Partner institutes totally to over 1500 CPUs and 60TB of storage. GARUDA has also laid the foundation for the next generation grids by addressing long term research issues in the strategic areas of knowledge and data management, programming models, architectures, grid management and monitoring, problem solving environments, tools and grid services. To ensure progressive evolution and durable integration, GARUDA is managed by C- DAC with the Grid monitoring and Management Centre at Bangalore. The GARUDA network is a Layer 2/3 MPLS Virtual Private Network (VPN) connecting select institutions at 10/100 Mbps with stringent quality and Service Level Agreements. This Grid is a pre-cursor to the next generation nationwide Gigabit Network with high performance computing resources and scientific instruments for seamless collaborative research and experiments. The key deliverable of this project include grid tools and services to provide an integrated infrastructure to applications and higher-level layers, a pan-Indian communication fabric to provide seamless and high-speed access to resources, aggregation of resources including compute clusters, storage and scientific instruments, creation of a consortium to collaborate on grid computing and contribute towards the aggregation of resources and grid enablement and deployment of select applications of national importance requiring aggregation of distributed resources 5. HPC Systems Research Procurement of HPC systems has to be augmented with strong systems research for sustenance, maintenance and enhancement of HPC capabilities, development of indigenous solutions, and attainment of cost-effectiveness. Realizing this, various Indian HPC centers and academic institutions conduct HPC system-oriented research to support high performance of applications. The areas of research include hardware systems, namely, development of high performance network stack or software, co-processors, switches, reconfigurable systems, multithreaded and distributed shared memory architectures, and programming models for general purpose architectures, software solutions, namely, message passing libraries, debugging environments and monitoring tools, and grid middleware, namely, and grid middleware, namely scheduling and fault- tolerance. 5.1 HPC Hardware Systems Research Centre for Development of Advanced Computing (CDAC) has built different system software products including network stack, monitoring and debugging frameworks and reconfigurable computing systems (RCS). CDAC has developed its own system area network called ParamNet. The latest version, ParamNet-3 can provide up to 10 Gbps bandwidth for high performance communications. PARAMNet-3 has tightly integrated hardware and software components. The hardware components consist of Network Interface Cards (NIC) based on Communication Co-Processor “GEMINI”, and modular 48-port Packet Routing Switch. The software component “KSHIPRA” is a lightweight protocol stack designed to exploit capabilities of hardware and to provide industry standard interfaces to the applications. KSHIPRA communication substrate designed to support low latency and high bandwidth is the key to the high level of aggregate system performance and scalability of C-DAC HPCC software. C-DAC has also pioneered the RCS technology for HPC in the country, through its state- of-the-art design of hardware, system software and hardware libraries called Avatars. These Avatars are dynamically changeable circuits, corresponding to the compute intensive routines of the application codes. A great advantage that C-DAC’s RCS offers compared to other technologies for application acceleration is in terms of tremendous saving on power and space at the same time increasing application performance by many folds. Research at academia in India has been focusing on issues relating to architecture design, performance evaluation of HPC systems. Here we report the research activities of two groups at the Indian Institute of Science (IISc), Bangalore. The High Performance Computing group at the Supercomputer Education and Research Centre (SERC) worked on the design of simultaneous multithreaded architectures and software distributed shared memory architectures on distributed memory machines. More recently their interest are on the design of high performance systems using off-the-shelf general purpose accelerators such as the Graphics Processing Units (GPUs), the Cell Broadband Engine, RapidMind, ClearSpeed, Imagine, etc. These accelerators support tens to 100s of cores in a processor and a complex memory hierarchy largely optimized for higher bandwidth. However, these architectures limited support for general purpose programming models. A major challenge in using accelerator architectures is programming and exploiting performance from them. The non-existence of standard toolchains and frameworks also makes programming on these processors makes this problem extremely difficult and challenging. The HPC group at SERC has been working on developing programming models and compiling techniques for HPC systems with accelerators. The Computer Aided Design Laboratory (CAD Lab) at SERC has been working on reconfigurable architectures and accelerator architecture designs based on reconfigurable architectures. The supercomputing platform envisaged with such a design would be “future proof” both in terms of hardware and software, scalable, and runtime reconfigurable. The goal of this exercise is to build a prototype general purpose supercomputing platform that can manifest as application specific hardware accelerators for every application running on it. The current focus is on SoC Design Methodologies, Micro-architectural optimizations for Cache hierarchy in Chip Multiprocessors (CMPs) and Multiprocessor SoCs (MP-SoCs). Research is also underway on supporting multiple computing paradigms (simultaneously) on MP-SoC platforms and Dynamically Reconfigurable SoC Architectures. 5.2 HPC System Software Research C-DAC High Performance Computing and Communication (HPCC) software effectively addresses the performance and usability challenges of clusters through a high performance flexible software environment. The HPCC software suite of products includes high performance compilers, parallel debuggers, data visualizers and performance profilers. High performance communication protocols and efficient MPI implementation provide the correct framework to extract maximum performance. In this direction, CDAC has also developed its own implementation of Message Passing Interface (MPI) standard, C-MPI, for parallel computations on Cluster of Multi Processors (CLUMPS). CDAC’s DiViA is a complete debugging environment for enterprises that need to develop parallel application using message-passing and provides portability, execution visualization and performance analysis. The PARMON tool of CDAC is a comprehensive cluster monitoring system and is designed using state of the art Java technology and offers portable, flexible, and comprehensive environment for monitoring of large clusters. It follows client-server methodology and provides transparent access to all nodes to be monitored from a monitoring machine. MetricAdvisor is a software engineering toolset for developing high quality programs. . 5.3 Grid Middleware The National Grid projet, Garuda, has developed grid middleware components for seamless solution of large-scale applications on the distributed high performance resources. Garuda Components The Service Oriented Architecture (SOA) is a component based model for building an application architecture within which all functions are defined as independent number of discrete services with well defined invokable interfaces, that can be called in a sequence to form a larger application. Grid middleware is now moving towards Web Standards based on OGSI (Open Grid Standards Architecture) and WSRF (Web Services Resources Framework). A service oriented architecture is enabled on GARUDA using the Globus Toolkit 4.0.3 as the grid middleware. The GARUDA Portal is the single point entry to Garuda resources and implemented services. The Garuda Grid Portal provides a web-based environment for users to submit and track jobs in the GARUDA. The GARUDA portal which provides the user interface to the Grid resources hides the complexity of the Grid from the users. It allows submission of both sequential and parallel jobs and also provides job accounting facilities. Gridway open source scheduler for grid has been customized and deployed in selected resources of GARUDA and configured in a peer-to-peer mode to support high availability of compute resources. A QoS framework supporting resource reservation has been enabled. Program Development Environment including a Grid Integrated Development Environment and a Grid Program Debugger have been developed. Data grid solution using Storage Resource Manager (SRM), iRODS and Grid File System GARUDA Job Submission Portal To enable data oriented applications, GARUDA provides an integrated but distributed data storage architecture by deploying the Storage Resource Broker (SRB) from Nirvana. SRB creates and maintains a Global Namespace across multiple heterogeneous and distributed storage systems in the Grid. The SRB provides advanced services including transparent data load and retrieval, data replication, persistent migration, data backup and restore, and secure queries. GARUDA has adopted a pragmatic approach for using existing Grid infrastructure and Web Services technologies. The resource management and scheduling in GARUDA is based on a deployment of industry grade schedulers in a hierarchical architecture. At the cluster level, scheduling is achieved through Load Leveler for AIX platforms and Torque for Linux clusters. At the Grid level, the Moab scheduler from Cluster Resources interfaces with the various cluster level schedulers to transparently map user requests onto available resources in the Grid. The Indian Grid Certification Authority (IGCA) accredited by the APGridPMA has been setup in C-DAC Bangalore. The IGCA will help scientists, users and collaborative community in India and neighboring countries, to obtain an internationally recognized digital certificate to interoperate with state-of-the-art grids worldwide. The IGCA was inaugurated on 14 Jan 09, by Dr. R Chidambaram PSA to Govt. of India and presided by Secretary DIT. This is the First CA in India for the purpose of Grid research. IGCA is fully operational and issuing digital user and host Certificates to support the secure environment in Grid. GARUDA grid is monitored using an in-house developed comprehensive Grid Monitoring Tool called Paryavekshanam. The tool monitors all the compute-storage- instrument resources, network and grid middleware & software. The Alert and Notification System of escalates the errors and warning to concerned administrators for speedy rectification. A dedicated Grid monitoring and management centre at C-DAC, Bangalore, with state-of-the-art display walls helps in managing and monitoring all the components in the Grid. Display wall at GMMC Paryavekshanam Tool The Grid Applications Research Lab (GARL) in SERC, IISc, conducts grid middleware research for high performance computing. It has developed optimized MPI collective communication algorithm for one-many and many-many communications for grids. It has built performance modeling strategies for automatically characterizing the behavior of parallel application executions on Grids. It has also developed scheduling algorithms and rescheduling strategies for parallel applications on grid systems. The work on rescheduling strategies is the first work on handling both application and resource dynamics for parallel applications on grid resources. GARL also conducts research on and has developed software for checkpointing, fault-tolerance and migration of parallel applications on heterogeneous and dynamic grid resources. With these robust grid middleware techniques, GARL aims for large-scale deployment and widespread use of parallel applications on computational grids by the scientific community. GARL has developed a grid middleware framework called MerITA (Middleware for Performance Improvement of Tightly-Coupled Parallel Applications on Grids) encompassing the performance modeling, scheduling and rescheduling techniques for efficient execution of long-running scientific applications on multi-cluster grids consisting of dedicated or non- dedicated, interactive or batch systems. The Department of Computer Science and Enginnering, IIT Kanpur, conducts research and has developed solutions for checkpointing parallel applications on grid resources, automatic program parallelization tools, workflow development framework and scheduling methodologies for composing applications on grids, modeling and verifying complicated workflows, frameworks for fault-tolerance and hierarchical dynamical scheduling, performance modeling and energy-aware scheduling for grids. [RG: Janakiram’s page is not opening up.] 6. HPC Applications India’s HPC procurements are predomiantly geared towards supporting the high performance application needs of the country. The different HPC centers of India specialize in various cutting-edge scientific applications. Many applications are developed in-house by application groups to enhance the scientific potential in their respective domains. Some applications are built from mostly off-the-shelf open-source components for various scientific domain to help the domain scientists perform studies related to the Indian context. In this section, we describe the activities related to three primary areas, namely, climate modeling and weather forecasting, bioinformatics, and computational chemistry. 6.1 Climate Modeling and Weather Forecasting Climate research in India is focussed towards understanding and forecasting the Indian summer monsoons. A widely accepted view is that simulation and forecast of the Indian summer monsoon is one biggest challenges facing atmospheric/climate modellers worldwide. This research is being conducted by Indian researchers using state-of-the-art models for the climate system. They also use global and regional atmospheric models for forecasting and research. Oceanographers in India have used ocean models and climate system models to study the circulation processes in the Indian Ocean. Indian researchers were one of the earliest in the world to use parallel processing techniques for climate modelling and have always been innovative in the use of upcoming technologies to study monsoon and climate. Forecasting of Weather/climate is done by India Meteorological Department (IMD) and National Centre for Medium Range Weather Forecasting, Noida (NCWRF). Ocean state forecasting is being conducted at Indian National Centre for Ocean Information Systems, Hyderabad (INCOIS). Major centres for climate research are CDAC, CSIR Centre for Mathematical Modelling and Computer Simulation (CMMACS), Indian Institue of Tropical Meteorology, Pune (IITM), Indian Institute of Technology, Delhi (IIT-D), Indian Institute of Science, Bangalore, National Aerosopace Laboratories, Bangalore (NAL) and Space Application Centre, Ahmedabad (SAC). CDAC has successfully implemented many atmospheric and oceanographic application on its Param series of supercomputers. The models implemented include WRF, the NCMRWF model and the Community Climate System Model (CCSM). Work is also underway to develop a regional climate model using Regional Ocean Modelling System (ROMS) and Regional Climate Model (RegCM). An end-to-end forecasting product (based primarily onWRF) called `Anuman', has been developed at CDAC-Pune. Ocean model of Insitute of Numerical Mathematics of Russia has been succesfully implemented on their computing platforms. Studies on parallel implementation and scalability have also been conducted here. Application of grid to climate studies is also being peformed on the Garuda Grid. CDAC was a major player in the country's first atmospheric modelling intercomparison project called SPIM (Seasonal Prediction of Indian Monsoon). This involved successful implementation and seasonal scale ensemble simulations of five AGCMs belonging to various organizations. This exercise was carried out by CDAC on its Param-Padma supercomputer. Community Climate System Model (CCSM) of NCAR, Climate Forecast System (CFS) and Seasonal Forecast Model (SFM) and UKMO atmosphere/ocean model are some of the prominent applications available on PARAM Padma computing systems. INCOIS is involved in the mathematical modeling of the climate system (individually / coupled) to obtain better understanding over the less observed regions, since the present network of observations in the ocean is not sufficient to understand the ocean dynamics and thermodynamics completely. Some of the objectives of the INCOIS’s HPC system include ocean modeling for providing description of past, present and future state of ocean at appropriate spatial and temporal resolutions, assimilation of in-situ and remotely sensed data (Argo Profiling Floats, Moored Buoys, Ship Observations, Satellite Measurements, etc) with the help of suitable ocean general circulation models, providing boundary forcing for atmospheric models by performing forecast runs of ocean models, understanding variability of Ocean and Marine environment, simulation experiment to optimize the observation system and serving as a National Computational Facility for ocean models. INCOIS uses various high performance ocean models including MOM, ROMS, CUPOM and HYCOM, WAM, WAVEWATCH-III and Tsunami N2 model. NCMRWF (www.ncmrwf.gov.in) is entrusted with the task of generating medium range forecasts (3-15 days).. Global weather models at a resolution of about 50 km are being used here. Regional weather models with even higher resolutions are also being used for shorter range forecasts upto 3 days. IMD (www.imd.gov.in) Delhi generates short-range forecasts upto 3 days while IMD Pune generates seasonal forecasts upto 90 days using numerical models. SAC (www.sac.isro.gov.in) : The emphasis at SAC is on the use of satellite data for weather/climate studies. Both regional and global models are used for study on the impact of ingesting satellite products on weather forecasting and climate studies. Seasonal forecasts are also generated here in collaboration with NCMRWF. IITM (www.tropmet.res.in) conducts research on tropical meteorology (and oceanography) with emphasis on Indian summer monsoons. Studies are also being conducted on the likely impact of anthropogenic climate change on the Indian Summer monsoon. Regional weather models, global atmospheric models (AGCMs) and coupled ocean atmosphere models are being used at this centre. CMMACS (www.cmmacs.ernet.in): research is conducted here both in meteorology and oceanography. Meteorological studies includes research on seasonal forecasting of monsoons and likely impact of anthropogenic aerosols on the strength of the monsoons. Oceanographical studies involve studies related to circulation in the Indian Ocean, bio- geo-chemical processes in the ocean and data assimilation. At the Indian Institute of Science (IISc), researchers in the Centre for Atmospheric and Oceanic Scinces, researchers work on ocean, atmospheric and coupled systems. The emphasis is on understanding mechanisms that govern various processes that affect the Indian summer monsoon. AGCMs, OGCMs and coupled climate system models and regional weather models are used for these studies. Issues such as the impact of anthropogenic (black carbon) aerosols on the Indian Summer monsoon, impact of atmosphere on oceanic parameters over the Indian region, study of the Indian Ocean Dipole, impact of African and Himalayan orography on monsoons etc have been carried out using these models. India's first parallel implementation of a climate model was conducted by IISc in collaboration with NAL and the first major climate system (coupled model) simulation conducted in association with CDAC. Studies have successfully conducted to increase scalability of atmospheric models using message-compression techniques. A new load balancing algorithm has been been developed and successfully implemented in a climate system models (one of the few such exercises conducted worldwide on a coupled climate system model). Currently work is underway to grid-enable a climate system model. This involves not only modifying the cimate system model but also development of related middleware to facilitate concurrent execution of subsystems at multiple sites (. NAL (www.nal.res.gov.in) has been developing its own parallel computing system, Flosolver, for over two decades. Both hardware and related software are developed here. The hardware and software design has been done keeping meteorological applications such as the spectral global prediction models in mind. The novelty of the communication switch developed here (called the Floswitch) is that global operations (such as global sums, max, min etc) are conducted on the switch itself and the resultant information is sent to the computing elements. This significantly reduces bandwidth demands. Atmospheric models have been re-engineered and re-coded here. Starting with NCEP global weather forecast model, a new model called VARSHA, has been developed. The latest version under development uses object-oriented programming concepts. Research mode forecasts are being generated on medium range and seasonal scales using these models. IIT-Delhi (www.iitd.ac.in) : AGCMs and regional weather models are used at this centre for study of monsoons and intense weather systems over the Indian region. A global spectral model has been successfully implemented based on longitudnal decomposition instead of the conventional latitudinal decomposition. Scalability studies for such a decomposition have also been conducted. Using these models issues such as impact of Eurasian snowcover on the Indian monsoon have been addressed. Ocean models are also being used to study coastal and large-scale circulation of the Indian Ocean. Future Directions The emphasis for Indian climate researchers will continue to be on monsoons. Even today, most climate system models have major problems in simulating the Indian summer monsoon. The looming worry of anthropogenic climate change, specifically its impact on the Indian summer monsoon is a matter of added concern. These factors imply that models need to be improved further. Researchers would be interested in including more sophisticated implementation of various processes such as the sub-grid scale cumulus parameterization and boundary layer parameterization, improved numerical techniques, incorporation of additional tracers in the atmosphere (such as aerosols) and ofcourse higher spatial resolution. These would increase demands on computational resources. HPC researchers (specifically in the field of climate studies) would need to look at innovative techniques such as grid computing (modest beginnings have already been made) and use of GPUs and cell-processors. Grid-computing could help agglomerate resources that may not be available at a single site. GPUs and cell-processors could be effectively used by applying multi-threading techniques to hive off computationally intensive sub-components to these processors. The GCMs software being developed using Object-Oriented techniques would ease the job of researchers in implementing new ideas in their models. More automatic weather stations are likely to be installed all over the country. New satellites such as the Indo-French Megha-Tropique are to be launched to study monsoons. A network of Doppler radars is being setup to monitor intense weather events. An array of deep-sea sensors are in the process of being deployed for tsunami and ocean-state forecasting. All these would need to integrated into an instrument grid which in turn would need to be interfaced to a datagrid for effective utilization of these new resources. 6.2 Computational Chemistry Research problems pursued in the computational chemistry/physics area can be broadly classified into two; (i) Study of electronic structure,and (ii) Dynamics of complex systems. In the former, traditionally the focus has been on crystalline solids and of late on nanostructured materials, primarily by practitioners of computational physics using approaches such as tight binding theory, muffin tin orbitals, many body calculations and so forth. Another independent stream of workers interested in electronic structure are quantum chemists, whose primary interest used to be small molecules studied using semi- empirical, Hartree-Fock (HF) or post HF methods. The advent of density functional theory (DFT) with extremely robust exchange-correlation functionals has energised these two distinct communities and have led them to investigate non-traditional atomic and molecular architectures in the areas of nanomaterials, supramolecular systems and so forth. The second direction of research in computational chemistry/physics is the study of complex systems. Until a decade ago, many research groups used to study the structure and dynamics of simple liquids, both atomic as well as molecular ones, using primarily the technique of molecular dynamics (MD) or alternately using Monte Carlo (MC). These methods employ an empirical interatomic potential of interaction and the time evolution of the system was studied. In the recent past, this category of researchers have been increasingly focussing on phase behavior, mesoscale structure (morphology) and slow dynamics in complex systems. This development has been made possible due to many factors such as (i) faster algorithms (such as FFTs for calculating Coulomb interactions), (ii) better single processor performance, (iii) easier availability of MPI based public domain codes, and (iv) commoditization of HPC hardware and support software (such as compilers, libraries etc..). Some of the activities in these research areas are presented in brief below. State-of-the-art multireferenced Coupled-Cluster calculation of accurate electronic structure of atomic systems are important for spectroscopic studies, lifetimes of energy levels, transition probabilities, polarizabilities and to probe particle and nuclear physics by combining with experimental measurements. Coupled cluster at Singles and Doubles (CCSD) level for both relativistic and non-relativistic methods have been ported and executed on PARAM Yuva cluster. Extensive ab initio calculations on nanomaterials using density functional pseudopotential plane wave method on a variety of Al-Au clusters have shown exceptional stability of 58 valence electron (leaving the 5d electrons of Au) clusters such as an empty cage doubly charged icosahedral fullerene Al12Au20 and an endohedral Al12Au21 - fullerene anion in which a gold atom lies at an off-center position inside the Al12Au20 cage. Formation of such caged structures by metal atoms is very unusual and novel. Further detailed studies on different endohedral dopings as well as other caged and small clusters of Al-Au and Al-transition metals have been carried out. Stabilities of Al-Au clusters having 18, 20, and 40 valence electrons corresponding to magic behavior in a jellium model, have been explored. Studies on many other systems in bulk and nanoforms are also being conducted. CMSD, Hyderabad, conducts research in various aspects of electronic structures including physics of low dimensional systems, topological defects in restricted geometries, critical phenomena, quantum chemistry, molecular modeling and design of new materials. The cluster at CCMS, JNCASR, is exclusively devoted to carrying out computations related to materials science. Typical application software include CPMD, LAMMPS, Quantum Espresso, SIESTA, VASP, and ADF and many home brew codes. Broadly they fall into two categories: those based on quantum mechanical approaches and those which are not – an example of the latter being LAMMPS. All codes have been found to scale rather well, provided the problem size is large enough. CPMD, SIESTA, and Espresso are based on density functional theory and are used to study the details of electronic and atomic structure and dynamics of various advanced materials, including metal-DNA complexes, multiferroics, surfaces, nanocatalysts, ionic liquids etc. LAMMPS is used to model supercritical carbon dioxide, room temperature ionic liquids and various glass forming liquids using empirical potential molecular dynamics. VASP is used to study many magnetic and other materials possessing interesting electronic structure, while ADF which is based on quantum chemical approaches is used to study molecular complexes. CPMD and LAMMPS have exhibited linear scaling for large problems. An important component of the activity at JNCASR is computational materials design in which novel atomic and molecular architectures are crafted and their properties studied using the techniques described above. It is then a challenge to experimental researchers to come up with strategies of synthesizing such compounds in the laboratory. At the Indian Institute of Technology, Kanpur, the HPC facilities are extensively used to carry out computational studies on chemical dynamics in condensed phases, surface adsorption and related kinetic processes, chemical reaction dynamics in gas phase, structure and energetics of biologically relevant molecules and many other key problems in chemical sciences and related areas. While Gaussian03 has been used for high level quantum chemical calculations of molecules and clusters at zero temperature, CPMD, VASP and Quantum Espresso are used for finite temperature simulations clusters and condensed phases using full many-body quantum potentials. These later packages are also used for many of the static pseudopotential based quantum calculations of chemically interesting systems which appeared to be too large for explicit all-electron calculations. For very large systems, such as interfaces, solutions of complex solutes etc, AMBER, DLPOLY or GROMOS are used for empirical potential based dynamical simulations. An interface of GROMOS-CPMD is also used combined classical-quantum simulations of many of the chemical systems of interest such as proton transfer through narrow hydrophobic pores. Up to 24 processors for a single job for quantum were used and combined classical-quantum simulations and the scalability has been found to be very good in this domain. In addition to the above software, homemade application codes are also heavily used for various computational studies. Future Trends As alluded to in the Introduction, in the area of electronic structure theory and computation, synergistic interactions between traditional computational physics and chemistry groups are taking place. This could eventually lead to new methods being developed. Another significant development has been the ability to carry out ab initio MD simulations of many chemical systems. One can expect computational studies of enzymatic reactions using realistic QM/MM approaches in the near future. Although a significant amount of work has been accomplished by Indian researchers in the area of computational chemistry (both in terms of development of methods and in applications), contributions towards the development of algorithms and large codes have been lacking. One way to tackle this lacuna is probably to co-opt with the famed Indian software industry. Efforts in this direction are paramount if Indian computational chemistry research has to make a global impact, in a qualitative manner. On the whole, one can expect major contributions in computational chemistry research from India in the near future. FIGURE 1: Large scale coarse grained MD simulations have led to the accurate characterization of the phase of a room temperature ionic liquid to be lamellar in nature (S. Balasubramanian et al, JNCASR, Bangalore) FIGURE 2: Accurate quantum chemical calculations have been able to explain the variation of Raman signals from two-dimensional graphene in the presence of donor and acceptor molecules (S.K. Pati et al, JNCASR, Bangalore) 6.3 Bioinformatics, BioScience and Genomics Computational-science studies carried out in the biological sciences area at the Indian Institute of Science include molecular-dynamics (MD) and electronic-structure calculations of proteins and nucleic acids, systems-biology investigations such as simulations of virtual cells, drug discovery and rational-vaccine design via virtual screening- ligand docking, ab-initio ligand design, and epitope design and detection in pathogenic genomes, the elucidation of the relation between sequence, structure, and function has been carried out by genome-sequence analysis, structure prediction, protein- protein interaction, phylogenetic profiling, biological image analysis, feature detection. Some specific examples of the studies carried out are given below: the dynamics of the top three sidechain clusters of Met-tRNA Synthetase, which has 550 amino-acid residues, was simulated for 10 ns; MD simulations have been carried out for a variety of DNA sequences (about 32 base pairs) to study their intrinsic curvature in solution; hydrogen bonds between two amino acids have also been studied by such simulations: virtual screening, for drug discovery and design has been carried out for flexible ligand with sizes from10-50 atoms (flexible) and (rigid) proteins with sizes from 2000-5000 atoms (1 docking run requires roughly 106 energy evaluations, and so far only a modest ligand database of about 100 compounds has been used with rigid, not flexible, proteins); similarly rational vaccine design has been carried out by using a T-cell epitope prediction algorithm; phylogenetic profiling and molecular taxonomy has been done for 400 bacterial genomes; a computer-intensive approach has been developed for the sensitive detection of extremely remote protein homologues; databases on protein structures, distant homology detection, domain architectures, multiple profiles of protein families and protein kinases are updated regularly. CDAC’c Param supercomputers also perform Multiple Expectation maximization for Motif Elicitation (MEME). MEME is an important application code for researchers working in the area of comparative and functional genomics, especially, gene regulation and microarrays. Study of Motif has implications in detection of transcription factor binding sites, gene-regulatory network, drug-target prioritization and drug-design. The National Center for Biological Sciences (NCBS) performs experiments in the applications of computational neuroscience and systems biology in its HPC clusters. It also conducts research in homotopy continuation searches for roots of systems of nonlinear equations, and in data mining and protein structure analysis related to bioinformatics. The Center for Modeling, Simulation and Design (CMSD), University of Hyderabad, uses it HPC clusters to conduct research in various bioinformatics applications including biosequencing analysis, structural and functional genomics to map protein coding regimes and sequencing of DNA, protein folding, computational design of specific drug molecules based on the drug-receptor interactions. SCFBIO has developed a genome analysis software suite called Chem Genome, a protein structure prediction software called Bhageerath, and an In-Silico drug design software called Sanjeevani. Chemgenome is based on the hypothesis that both the structure of the DNA and its interactions with regulatory proteins and polymerases decide the function of a DNA sequence. The ChemGenome could distinguish genes from non-genes in more than 900 bacterial genomes with > 90% accuracy. Bhageerath is an energy based computer software suite for narrowing down the search space of tertiary structures of small globular proteins. The protocol comprises eight different computational modules that form an automated pipeline. It combines physics based potentials with biophysical filters to arrive at 5 plausible candidate structures starting from sequence. The methodology has been validated here on 50 small globular proteins consisting of 2–3 helices and strands with known tertiary structures. Bhageerath, the protein structure prediction software developed in-house at IIT Delhi could run on a 1024 processor IBM Blue Gene. A three helical system which took around 5-6 hours on a 32 processor cluster took just 726 second (~12 minutes) on a 1024 processor Blue Gene machine. SCFBIO has also developed an atomic level binding free energy based methodology for active site directed lead molecule design (Sanjeevini). The various modules of this suite are designed to ensure reliability and generality. The software is currently being optimized on Linux and Sun clusters for faster and better results. The Sanjeevini protocols could sort drugs from non-drugs for a few drug targets helping in addressing both affinity and specificity issues in drug design. The web-enabled versions of the software suite developed by SCFBIO are available for free usage at www.scfbio-iitd.res.in. Besides these in-house packages SCFBIO also uses free available high performance software including Amber, Gaussian, Gromacs, Gamess. Study of Relationships between Bistable Chemical Systems NCBS, Bangalore 6.4 Grid Applications The Indian National Grid Middleware project, Garuda, has developed Problem Solving Environment (PSE) in the domains of Bio-informatics, and Community Atmospheric Model to support the entire cycle of problem solving for the specific domains by supporting problem formulation, algorithm selection, numerical simulation and solution visualization. Applications of national importance that require aggregation of geographically distributed resources have been developed and deployed on the GARUDA Grid. A Disaster Management application for Flood Assessment, a Bioinformatics application on Molecular Docking using OpenEye, E-Learning, Computer Aided Engineering, and applications in Atomic Physics have benefited from grid enablement in terms of improved performance and increased collaboration. C-DAC in association with a partner research institution has mined data from a network of sensors deployed over vast disaster prone regions and upload it to GARUDA as input to forecast models appropriate for various stages of Natural Disaster Management. This will enable timely dissemination of disaster information to user agencies for effective mitigation and relief measures. C- DAC’s Bio-informatics Resources & Applications Facility on their PARAM Supercomputing facility, is accessible for the Bioinformatics community involved in insilico molecule identification and new drug discovery. The enormity of data and complexity of algorithms in bio-informatics demand tremendous computational cycles necessitating effective use of grid resources beyond those available at any single location. Disaster Management Molecular Docking The Grid Applications Research Lab (GARL), SERC, IISc, develops solutions for the effective use of grids to solve large-scale scientific problems. GARL’s current research is on developing grid-based solutions for two applications, namely, climate modeling and phylogenetic predictions in bioinformatics. The research on climate modeling deals with various challenges associated with executing components of a coupled climate model on different grid sites and shows the benefits of grids for solving applications related to climate modeling. The research has developed a novel 3-level load-balancing strategy and has also conducted a novel study using a robust simulator for analyzing the potential benefits of executing the climate model on grids. GARL is also developing a general grid framework for efficient execution of multi-component applications like coupled climate models on grids. In the area of phylogenetic predictions in bioinformatics, GARL uses Grid resources to analyze neighbor-dependent mutations on different branches of a phylogenetic or evolutionary tree and use the analysis to predict future DNA sequences. 6.5 Other HPC Applications Disaster Management CDAC’s DMSAR is a RADAR based Airborne earth imaging system through which the real time situations of any natural and man induced disasters can be mapped even in rough weather conditions. Synthetic Aperture RADAR (SAR) fitted beneath aircraft captures data of flood region. DMSAR scans the terrain and capture the data in different resolution modes The minimum amount of data captured in a single run is 9GB of raw data. Data is processed by CDAC’S HPC centers to expedite decision making. Winglet Optimization The efficiency of an aircraft can be increased by decreasing the drag force of an aircraft. One of the ways to reduce induced drag is to have winglets at the tip of the wing. The design of the winglet requires the use of an optimization algorithm known as Genetic Algorithm. This algorithm automatically generates a huge amount of random winglet shapes. The performance of these winglet shapes and their effect on the overall aircraft design is then analyzed using Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) software. This whole framework, named Winglet Optimization System (WOS), which is the property of Zeus Numerix Pvt. Ltd. requires huge state-of-art super-computing facilities which is provided by CDAC. This has enabled us to execute the Winglet design work at an accelerated pace. Machine Learning CMSD, Hyderabad uses its HPC clusters to develop products and conduct research in cognitive neuroscience, computational intelligence, and natural language understanding. 7. HPC Industry in India The HPC industry have grown mature in India in the last 2-3 decades. Multinationals such as IBM, Cray, DEC, NEC, and SGI also had strong influence on the HPC market in the early 1990s. Indian companies, e.g., Hindustan Computers Limited (HCL), Wipro Technologies, Hindtitron Systems, Computer Maintenance Corporation (CMC), Tata ELXSI, were early players in the HPC market segment. However, in the early years, many of the Indian companies as well as the Indian outfits of the Multi-national companies were primarily enablers for the sale and after-sale services of HPC systems. However, all of these Indian companies or Indian outfits of the multinationals had a strong group on systems software. In fact, systems software has been a major strength of the Indian industry in the 1980s. In the last decade, with the advent of cluster computing, the scenario somewhat changed. Indian companies were getting involved in integration of cluster architectures. One of the notable successes in this front is the IMSC’s Kabru cluster where Summation Enterprises and Netweb Technologies were instrumental in the integration of cluster. Today, a number of cluster of various sizes have been integrated by various Indian companies as well as the multinationals in India. Organizations such as CDAC have also in-house expertise in cluster integration. Recently few companies including Yahoo! India and Amazon Development Center, India, have created strong research groups for research and development on cloud computing. Cloud computing involves creation of “clouds” of services that can be invoked remotely by customers for solutions. By virtualizing the remote, complex, distributed network of hardware and software resources, cloud computing offers cost- effective solutions for small and medium-scale companies to make use of the already created solutions for various applications, including, data-mining, web-search and retrieval of large-data sets. Cloud computing has huge potential for high performance computing wherein, high performance applications can be created as cloud services and these services can be invoked remotely on large high performance centers and data centers. 8. Top Supercomputers-India Top Supercomputers-India (http://topsupercomputers-india.iisc.ernet.in), developed in and by Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, is an effort to list the most powerful supercomputers in India. This effort is complementary to the Top500 project that lists the top 500 supercomputers in the world. The aim of Top Supercomputers-India, similar to Top500, will help create and promote healthy competition among the supercomputing initiatives in India and can substantially lead to significant supercomputing advancement in the nation. LinPack benchmark and the same submission and evaluation procedures in Top500 is used for ranking the systems. The number of machines in the TopSupercomputers-India list is based on minimum performance threshold. The project was announced in September and submissions were collected in the beginning of October 2008. After verification, the first list was released on December 18 in the Plenary Industrial Panel session of the International Conference on High Performance Computing (HiPC), 2008, held in Bangalore. Certificates containing the signatures of Dr. Jack Dongarra were given during the event. The first list contained 11 entries and the current and the second list contains 13 entries. The top entry is the EKA supercomputer of Computational Research Laboratories Ltd (CRL), a wholly owned subsidiary of TATA Sons Ltd. The first four in the list are also in the Top500 list. The combined performance of the machines in the list is 243.71 TeraFlops. Five of the systems are from Centre for Development of Advance Computing (CDAC), proving its status as a leading high performance computing center in the nation. Top Supercomputers-India: June 2009 List Cores/Processor Rmax Rpeak Rank Site System Sockets/Nodes (TFlops) (TFlops) HP Cluster Platform 3000 BL460c (Dual Computational Intel Xeon 3 GHz Research 1 quad core E5365 14400/3600/1800 132.80 172.60 Laboratories Ltd, (Clovertown) Pune w/Infiniband 4X DDR) Center for PARAMcluster (Intel Development of Xeon (Tigerton) 2.93 2 Advanced GHz quad core quad 4608/1152/288 37.80 54.01 Computing (C-DAC) processor X73xx India nodes w/Infiniband) IBM eServer Blue Gene Solution, BlueGene/L (IBM Indian Institute of 3 PowerPC 700 MHz 8196/4096/4096 17.81 22.94 Science, Bangalore 440x5 processors w/Proprietary Interconnect) BL460c (Xeon 54xx Paprikaas Interactive 4 3.0GHz 1920/ / 13.16 23.04 Services India w/GigEthernet) IBM Blue Gene Solution, Tata Institute of BlueGene/P (IBM Fundamental 5 PowerPC 850 MHz 4092/1024/1024 11.32 13.5 Research (TIFR), 450 processors Mumbai w/Proprietary Interconnect) Indian Institute of HP 256 Intel Xeon 6 1024/256/128 8.62 12.29 Technology Madras, Processor E5472 (3 Chennai GHz w/Infiniband) Indian Institute of HP 256 Intel Xeon 7 Technology Madras, Processor E5472 (3 1024/256/128 4.55 8.64 Chennai GHz w/Gigabit) HP Proliant DL140 Jawaharlal Nehru G3 (dual processor Centre for Advanced dual core Intel Xeon 8 Scientific Research 512/256/128 3.86 6.00 3GHz 5160 nodes (JNCASR), w/Infiniband 4X Bangalore DDR) Institute of HP CP3000 (576 Genomics and Intel Xeon Processor 9 576/576/288 3.06 4.08 Integrative Biology, X3.6GHz/800-2MB Delhi w/Infiniband) Centre for HP Cluster (Dual Development of Intel Quad Core 10 Advanced Xeon EM64 320/80/40 2.999 3.943 Computing (CDAC), processor Chennai w/Infiniband) Centre for HP Cluster (Dual Development of Intel Quad Core 11 Advanced Xeon EM64 320/80/40 2.976 4.044 Computing (CDAC), processor Bangalore w/Infiniband) Centre for HP Cluster (Dual Development of Intel Quad Core 12 Advanced Xeon EM64 320/80/40 2.614 3.94 Computing (CDAC), processor Hyderabad w/Infiniband) HP-DL580-G5 (Intel Centre for Xeon (Tigerton) Development of 2.933 GHz quad core 13 Advanced quad processor 256/64/16 2.165 3.00 Computing (CDAC), X7350 nodes Pune w/10Gbps PARAMNet-3) 9. Conferences and Events Several international conferences, workshops, and user fora have been held in India in the last 2 decades. Of these, the International Conference on High Performance Computing (HiPC), started in 1994 as a parallel processing workshop, and the International Conference on Advanced Computing and Communication (ADCOM), started in 1993, are annual conferences held in India. These conferences focus on an aspects of high performance computing and communications, and their scientific, engineering, and commercial applications. The HiPC conference features typically 50 research papers, 4-6 workshops, and an equal number of tutorials. In the recent years, the conference has attracted more than 300 submissions from 30 countries. . The conference is well attended with 250-300 participants, of which a significant number of them (more than 100) are from other countries. The ADCOM conference features typically 120 papers and 4-6 tutuorials and a 2-4 workshops every years. It attracts about of 400 submissions each year and has an attendance of 150-200 participants, of which about 75 or more are International participants. In addition to the above annual events, the 6th International Conference on High Performance Computing in Asia-Pacific Region (HPC-Asia) was held in Bangalore in the year 2002. The HPC User Forum Conference was held in New Delhi and Bangalore from Feb. 28 – March 2, 2007. Several computational science researchers from India have participated in this conference and presented their work. The forum also had industry participation and presentation. Overall these conferences have brough greater awareness on high performance computing in India. They have exposed the Indian graduate and undergraduate students to recent research work in HPC. They have served as a fora for the Indian HPC researchers to present their research and network with their peers. 10. Future Roadmap Various organizations plan to expand their HPC capabilities in the near future. CDAC aims to build a PetaFlop HPC facility by 2012. CMSD, Hyderabad, is currently augmenting its cumulative performance to 15 TeraFLOPS. INCOIS, CCMS at JNCASR, SCFBIO, and many of the other data centers that were surveyed in this report are planning to enhance their compute capability to a few 10s of TeraFLOPS. Their projected investment over the next 2-3 years would be ranging from 1 – 3 Million US$. We anticipate to see a 3-5 major centers which would host facilities with a few hundred TeraFLOPS to may be in the PetaFLOP range. At the same time, we anticipate a fairly large number of (may be 100 or so) smaller clusters of a few 10’s of TeraFLOPS. While the smaller clusters are like to be utilized for their full capability, with applications scaling to the number of cores in the clusters, the major challenge will be on the scalability of application on larger clusters/systems. We anticipate these systems will be used more for capacity (large number of jobs running on a few hundreds of cores) than for capability (jobs running on a few thousands of cores). This challenge needs to be addressed through training and specialized course programmes in computational science. Institutions like the Indian Institute of Science are offering Masters programs in computational science as an inter-disciplinary program. These programs are at their initial stages and are expected to yield fruits in the next 5 to 10 years. The government funding for HPC is expected to grow and support the above plans. . The Grid Garuda project is expected to go into the main phase with significant support from the government. The Grid project is expected to consolidate the resources across the country. The Grid communication fabric connecting various organizations will be enhanced to 10-100’s of Gigabits per second connectivity. The Garuda communication fabric and the Knowledge Network connectivity to various organizations will play a major role in ensuring a high-speed connectivity across the country. The emergence of Cloud computing and presence of international players will ensure cloud services being offered to research organizations on demand. It is not clear to what extent this (taking cloud services) will pick up in India, where research organization typically have an investment plan rather than going for a pay-per-use model. From the applications perspective, it is expected that more focus would be on computational aspects of seismic analysis, leading to earth quake and tsunami prediction, and climate change. In the computational biology area, the focus would be on drug and vaccine discovery through virtual screening for tropical and infectious diseases that are locally relevant. Sequence and structural analysis at genomic scale is likely to yield a holistic view of the functioning of a cell. Further, the simulation studies would move from macromolecules-level to macromolecular assemblies. In addition to the traditional computational problems, problems in the areas image and video analytics, applying machine learning techniques, applications enabling e-governance activities in various government functionaries, processing of information collected from distributed sensors are expected to draw more attention 11. TODOS a. Adding more in introduction with good general perspectives. – RG [DONE!] b. Section 5 - Some pictures?? c. Section 9 – Writing a good future roadmap section with good general perspectives. – RG [DONE!] d.