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CoopCL: Cooperative Execution of OpenCL Programs on Heterogeneous CPU-GPU Platforms

: Moren, Konrad; Göhringer, Diana


Institute of Electrical and Electronics Engineers -IEEE-:
28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2020. Proceedings : 11-13 March 2020, Västerås, Sweden
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2020
ISBN: 978-1-7281-6582-0
ISBN: 978-1-7281-6583-7
International Conference on Parallel, Distributed and Network-Based Processing (PDP) <28, 2020, Västerås>
Conference Paper
Fraunhofer IOSB ()
cooperative execution; workload splitting; heterogeneous computing; Multi-core CPU

In this work, we present CoopCL, an C++ API and runtime that abstracts and unifies the cooperative workload execution on multi-core CPU and GPU. The CoopCL takes a OpenCL-C kernel function and automatically uses both the CPU and the GPU to execute it in parallel. We propose a method that transparently manages the data transfers and synchronization necessary to ensure a coherence without requiring any effort from the programmer. The CoopCL is completely portable across different machines including platforms with discrete and integrated GPUs. Across a set of diverse benchmarks, our runtime shows a mean speedup of nearly 10% over a GPU only execution and 30% over a multi-core CPU. We also achieve up to a 52% reduction in energy consumption compared to the CPU only execution.