50 likes | 63 Views
Explore the potential of parallel databases in the context of distributed computing projects utilizing home PCs, current parallel processors, and parallel query processing at home. Discuss the challenges and opportunities in harnessing the power of commodity processors for high-performance computing.
E N D
Parallel Databases @ Home Qiong Luo Hong Kong University of Science & Technology http://www.cse.ust.hk/~luo
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
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
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
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