High Productivity Computing Systems Robert Graybill DARPA/IPTO March 2003

1. High Productivity Computing Systems Robert Graybill DARPA/IPTO March 2003

2. High ProductivityComputing Systems • Goal: • Provide a new generation of economically viable high productivity computing systems for the national security and industrial user community (2007 – 2010) Impact: • Performance (time-to-solution): speedup critical national security applications by a factor of 10X to 40X • Programmability (time-for-idea-to-first-solution): reduce cost and time of developing application solutions • Portability (transparency): insulate research and operational application software from system • Robustness (reliability): apply all known techniques to protect against outside attacks, hardware faults, & programming errors HPCS Program Focus Areas • Applications: • Intelligence/surveillance, reconnaissance, cryptanalysis, weapons analysis, airborne contaminant modeling and biotechnology Fill the Critical Technology and Capability Gap Today (late 80’s HPC technology)…..to…..Future (Quantum/Bio Computing)

3. Vision: Focus on the Lost Dimension of HPC – “User & System Efficiency and Productivity” 1980’s Technology Parallel Vector Systems Vector Moore’s Law Double Raw Performance every 18 Months Commodity HPCs Tightly Coupled Parallel Systems New Goal: Double Value Every 18 Months 2010High-End Computing Solutions Fill the high-end computing technology and capability gap for critical national security missions

4. HPCS Technical Considerations Performance Characterization & Precision Programming Models System Architecture Hardware Technology Software Technology Architecture Types Communication Programming Models Custom Vector Microprocessor Symmetric Multiprocessors Distributed Shared Memory HPCS Focus Tailorable Balanced Solutions Parallel Vector Shared-Memory Multi-Processing Massively Parallel Processors Commodity Clusters, Grids Distributed-Memory Multi-Computing “MPI” Scalable Vector Vector Supercomputer Commodity HPC Single Point Design Solutions are no longer Acceptable

5. HPCS Program Phases I - III Industry Evolutionary Development Cycle Early Academia Early Metrics and Benchmarks Metrics, Products Software Research Pilot Benchmarks HPCS Capability or Products Tools Platforms Platforms Requirements and Metrics Application Analysis Performance Assessment Research Prototypes & Pilot Systems Technology Assessments System Design Review Concept Reviews PDR DDR Industry Phase II Readiness Reviews Phase III Readiness Review Fiscal Year 02 03 04 05 06 07 08 09 10 Reviews Industry Procurements Critical Program Milestones Phase III Full Scale Development Phase I Industry Concept Study Phase II R&D

6. HPCS Phase I Industry Teams Industry: Cray, Inc. (Burton Smith) Hewlett-Packard Company (Kathy Wheeler) International Business Machines Corporation (Mootaz Elnozahy) Silicon Graphics, Inc. (Steve Miller) Sun Microsystems, Inc. (Jeff Rulifson) Application Analysis/Performance Assessment Team: MIT Lincoln Laboratory

7. Application Analysis/Performance Assessment Mission-Specific Roadmap Mission Work Flows Activity Flow Inputs Application Analysis Benchmarks & Metrics Impacts DDR&E & IHEC Mission Analysis Participants HPCS Technology Drivers Define System Requirements and Characteristics Common Critical Kernels HPCS Applications 1. Cryptanalysis2. Signal and Image Processing3. Operational Weather4. Nuclear Stockpile Stewardship5. Etc. Mission Partners: DOD DOE NNSA NSA NRO Compact Applications Applications • Productivity • Ratio of Utility/Cost • Metrics • Development time (cost) • Execution time (cost) • Implicit Factors Mission Partners Improved Mission Capability Participants: Cray HP IBM SGI Sun DARPA HPCS ProgramMotivation

8. Operational weatherand oceanforecasting Planning activities for dispersion of airborne/waterborne contaminants Cryptanalysis Intelligence, surveillance, reconnaissance Improved armor design Engineering design of large aircraft, ship and structures National missile defense Test and evaluation Weapon (warheads and penetrators) Survivability/stealth design Comprehensive Aerospace Vehicle Design Signals Intelligence (Crypt) Signals Intelligence (Graph) Operational Weather/OceanForecasting Stealthy Ship Design Nuclear Weapons Stockpile Stewardship Signal and Image Processing Army Future Combat Systems Electromagnetic Weapons Development Geospatial Intelligence Threat Weapon Systems Characterization Application Focus Selection IHEC Study DDR&E Study • Bioscience

9. Computational Biology: from Sequence to Systems Sequence Genome Assemble Genome Find the Genes Annotate the Genes Map Genes to Proteins Protein-Protein Interactions Pathways: Normal & Aberrant Protein Functions in Pathways Protein Structure Identify Drug Targets Cellular Response Tissue, Organ & Whole Body Response TeraOps Trivially Parallel 1 10 100 1000 Peta-Scale Computing Biomedical Computing Requirements Slide provided by IDC

10. HPCS Mission Work Flows Theory Code Prototyping Test Design Experiment Visualize Design Code Optimize Enterprise Development Prototyping Design Test Scale Simulation Orient Observe Production Evaluation Maintenance Decide Act Operation Overall Cycle Development Cycle Days to hours Hours to minutes Researcher Development Execution Port Legacy Software Port Legacy Software Months to days Months to days Design Initial Product Development Code Years to months Initial Development Hours to Minutes (Response Time) Test Port, Scale, Optimize HPCS Productivity Factors: Performance, Programmability, Portability, and Robustness are very closely coupled with each work flow

11. Workflow Priorities & Goals HPCS Goal Workstation Researcher Enterprise Cluster Productivity Production HPCS Problem Size Mission Needs Implicit Productivity Factors Workflow Perf. Prog. Port. Robust. Researcher High Enterprise High High High High Production High High System Requirements • Workflows define scope of customer priorities • Activity and Purpose benchmarks will be used to measure Productivity • HPCS Goal is to add value to each workflow • Increase productivity while increasing problem size

12. HPCS Productivity Framework System Parameters (Examples) Activity & Purpose Benchmarks BW bytes/flopMemory latencyMemory size …….. Execution Time (cost) Processor flop/cycle Bisection BW Total Connections ……… Productivity (Ratio of Utility/Cost) Actual System or Model Work Flow Productivity Metrics Size (cuft)Power/rackFacility operation ………. Development Time (cost) Code size Restart time (reliability) Code Optimization time ……… Implicit HPCS Productivity Factors: Performance, Programmability, Portability, and Robustness

13. HPC Community Reactions • DoD and DOE User Communities • Active participation in reviews • Providing challenge problems • Linking with internal efforts • Providing funding synergism • Industry • Finally an opportunity to develop a non evolutionary vision • Active program support (technical, personnel, vision) • Direct impact to future product roadmaps • University • Active support for Phase 1 (2X growth from proposals) • Extended Community • HPCS strategy embedded in Congressional IHEC Report Productivity a new HPC Sub-discipline