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- W4237011330 abstract "GPUs have become immensely important computational units on embedded and mobile devices. However, GPGPU developers are often not able to exploit the compute power offered by GPUs on these devices mainly due to the lack of support of traditional programming models such as CUDA and OpenCL. The recent introduction of the Vulkan API provides a new programming model that could be explored for GPGPU computing on these devices, as it supports compute and promises to be portable across different architectures. In this paper we propose VComputeBench, a set of benchmarks that help developers understand the differences in performance and portability of Vulkan. We also evaluate the suitability of Vulkan as an emerging cross-platform GPGPU framework by conducting a thorough analysis of its performance compared to CUDA and OpenCL on mobile as well as on desktop platforms. Our experiments show that Vulkan provides better platform support on mobile devices and can be regarded as a good cross-platform GPGPU framework. It offers comparable performance and with some low-level optimizations it can offer average speedups of 1.53× and 1.66× compared to CUDA and OpenCL respectively on desktop platforms and 1.59× average speedup compared to OpenCL on mobile platforms. However, while Vulkan's low-level control can enhance performance, it requires a significantly higher programming effort." @default.
- W4237011330 created "2022-05-12" @default.
- W4237011330 creator A5035769113 @default.
- W4237011330 creator A5053253139 @default.
- W4237011330 date "2018-09-01" @default.
- W4237011330 modified "2023-10-18" @default.
- W4237011330 title "VComputeBench: A Vulkan Benchmark Suite for GPGPU on Mobile and Embedded GPUs" @default.
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- W4237011330 doi "https://doi.org/10.1109/iiswc.2018.8573477" @default.
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