2015 · 53 citations · 33 references
ComputingComputer ScienceHigh-performance ComputingOperating SystemsParallel AlgorithmsParallel ComputingData ParallelismGraphics Processing Unit ComputingGraphics Processing UnitsKernel ProgrammingParallel Computing SystemsParallel Runtime SystemsBulk Synchronous Parallel AlgorithmsBulk Synchronous Parallel ModelBulk Synchronous ParallelismData-intensive ComputingDynamic ParallelismGpu ArchitectureGpu Runtime SystemsThread Parallelism
GPUs have been proven effective for structured applications that map well to the rigid 1D-3D grid of threads in modern bulk synchronous parallel (BSP) programming languages. However, less success has been encountered in mapping data intensive irregular applications such as graph analytics, relational databases, and machine learning. Recently introduced nested device-side kernel launching functionality in the GPU is a step in the right direction, but still falls short of being able to effectively harness the GPUs performance potential.
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An Algorithmic Framework for Performing Collaborative Filtering
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Analyzing CUDA workloads using a detailed GPU simulator
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Testing Intrusion detection systems
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