PySchedCL: Leveraging Concurrency in Heterogeneous Data-Parallel Systems

In the past decade, high performance compute capabilities exhibited by heterogeneous GPGPU platforms have led to the popularity of data parallel programming languages such as CUDA and OpenCL. Developing high performance parallel programming solutions using such languages involve a steep learning cur...

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Veröffentlicht in:	IEEE transactions on computers 2022-09, Vol.71 (9), p.2234-2247
Hauptverfasser:	Ghose, Anirban, Singh, Siddharth, Kulaharia, Vivek, Dokara, Lokesh, Maity, Srijeeta, Dey, Soumyajit
Format:	Artikel
Sprache:	eng
Schlagworte:	Central Processing Unit coarse-grained scheduling Concurrency Decisions Deep learning Engines fine-grained scheduling GPGPU Graphics processing units Kernel Learning curves OpenCL Parallel programming Platforms Processor scheduling Programming languages Schedules Scheduling Task analysis
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