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Parallel Databases @ Home

Parallel Databases @ Home. Qiong Luo H ong K ong U niversity of S cience & T echnology http://www.cse.ust.hk/~luo. Parallel Databases. Future of high performance computing [DeWitt and Gray, CACM 1992] Parallelism metrics: scaleup and speedup

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Parallel Databases @ Home

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  1. Parallel Databases @ Home Qiong Luo Hong Kong University of Science & Technology http://www.cse.ust.hk/~luo

  2. Parallel Databases • Future of high performance computing [DeWitt and Gray, CACM 1992] • Parallelism metrics: scaleup and speedup • Parallel architectures: Shared-memory, shared-disk, shared-nothing • Pipelined and partitioned parallelism • Intra-operator parallelism: split and merge • Specialized parallel operators All systems in this era ran in (super-)computer labs. Qiong Luo @ CIDR 2007

  3. Volunteer Computing @ Home • A bunch of distributed computing projects utilizing home PCs over the Internet (2000-) • SETI@home, 3 million users, TFLOPS-PFLOPS • folding@home • Einstein@home • LHC@home • Predictor@home • Rosetta@home • … All tasks are running on private computers at volunteers’ homes. Qiong Luo @ CIDR 2007

  4. Current Parallel Processors @ Home • CUDA • NVDIA GeForce 8800 video cards (Nov 06) • 16 SIMD multiprocessors, each of eight processors • Over 300 GFLOPS (10 X Intel 3.0GHz Core 2 Duo) • CBEA (The Cell Architecture by STI) • Sony Playstation3 game console (Oct 06) • One Power Processing Element (PPE) • Eight Synergistic Processing Elements (SPEs) Commodity processors with massive parallel processing power Qiong Luo @ CIDR 2007

  5. Parallel Query Processing @ Home ? • There are probably applications for it. • We might or might not need a full-fledged parallel database system. • There will be a learning curve for the emerging hardware architectures. • The @home computing paradigm requires us to rethink many issues. • There is a wealth of literature on parallelDB. Comments are welcome! Qiong Luo @ CIDR 2007

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