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High Performance Computing On Laptops With Multicores & GPUs

High Performance Computing On Laptops With Multicores & GPUs. Sushil K. Prasad Computer Science sprasad@gsu.edu. About me. Research Area: Parallel and Distributed Algorithms and Systems - over multicores , GPUs, clusters, sensors, handhelds, web services, …

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High Performance Computing On Laptops With Multicores & GPUs

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  1. High Performance Computing On Laptops With Multicores & GPUs Sushil K. Prasad Computer Science sprasad@gsu.edu

  2. About me Research Area: Parallel and Distributed Algorithms and Systems - over multicores, GPUs, clusters, sensors, handhelds, web services, … Lab: Distributed and Mobile Systems (DiMoS) at Ga. Tech campus, 5 PhD students, 2 M.S. students • IEEE TCPP Chair (elected) • 2 NSF grants – currently looking for PhD/MS/undergraduate students • Distributed Algorithms • High Performance Cloud Computing

  3. Multicore & GPU Chips Inside a Laptop - 100s of processors

  4. GPUs Vs Multicores • Combined power exceeds 180 GFLOPs

  5. Intel Core-2 Duo Multicore • Difficult to parallelize • Memory hierarchy is a barrier: • 1 cycle core • 3 cycles L1 cache • 14 cycles L2 • 250 cycles RAM

  6. GPU: Graphics Processing Unit • Nvidia 280 GTX • 240 cores • Extreme memory hierarchy • Registers • Local memory • Shared memory/8 cores • Off chip Global Memory • bottleneck bus to CPU

  7. Nvidia 8800 GTX • Smith Waterman Seq Alignment, Fasta, and Blast • Database: SwissProt • Manavskiand Valle 2008

  8. 2 6 7 5 5 6 3 8 8 1 7 9 14 10 9 65 34 38 19 21 12 12 15 16 13 14 23 25 Parallel Data Structures -Priority Queues • Large Scale Event Simulation • Immune System Simulation • VLSI Logic simulation • Branch and Bound • Task Scheduling • Challenge: Fine Grained Systems • Students: DineshAgarwal, Nick Mancuso

  9. Parallel Priority Queues on Multicore

  10. Legacy-Code to GPUs(Student: Chad Christopher)

  11. Distributed Algorithms for Lifetime of Wireless Sensor Networks (Student: AkshayeDhawan)

  12. NP-Hard Distributed Problems in Networks NSF Grant • Minimum Vertex/Target Cover • Minimum Triangle Packing • Optimum mobile sensor network target tracking • Minimum channel assignment in mobile ad-hoc networks • Students: John Daigle, ThamerSulaiman

  13. 2. Lookup 1. Register Middleware for Mobile Ad–hoc Applications Mobile Support Station Applications Deviceware Process Requests 3. p2p communication Listener Applications Applications Deviceware Process Requests Listener Deviceware Groupware Process Requests Listener Listener Process Requests UM-Morris Directory

  14. BondFlow: Distributed Workflow over Web Services(Student: JanakaBalasooriya) • Web service interface module • Proxy object generator module • Workflow configuration module • Execution module. • Mobile Web Services Web Service Interface Module Lookup for Web services Web Services Registry (UDDI) S O A P WS Locator WSDL WSDL Parser Parsed WSDL Workflow Execution Module Proxy Object Generator Module Web Bond Runtime SOAP/ SyD Workflow Configuration Module JVM

  15. A Priori Uncertainty : U1 A Posterior Uncertainty : U2 U1 –U2 = Information P2P Search based on Bayesian Decision and Value of Information (VOI) – (Student: Rasanjalee) The meaning of Uncertainty based Information • Peer Selection: • Sending/forwarding query at each node along query path = series of decision making steps based on incomplete data • A decision step: query the node that will reduce the uncertainty of current belief most. • Experimental Results: The reduction in uncertainty at each decision step Current Belief Decision step 1 . . . . Decision step n

  16. Middleware on Distributed Smart Cameras • Middleware on DSC networks • provide a high-level programming interface for applications. • simplify the development of distributed applications on DSC networks. • provide networking functionality as part of the middleware • Student: JayampathiSampat cmucam3

  17. About me Research Area: Parallel and Distributed Algorithms and Systems - over multicores, GPUs, clusters, sensors, handhelds, web services, … Lab: Distributed and Mobile Systems (DiMoS) at Ga. Tech campus, 5 PhD students, 2 M.S. students • IEEE TCPP Chair (elected) • 2 NSF grants – currently looking for PhD/MS/undergraduate students • Distributed Algorithms • High Performance Cloud Computing

  18. High Performance Computing On Laptops With Multicores & GPUs Sushil K. Prasad Computer Science sprasad@gsu.edu

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