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- W2023241094 abstract "When implementing data-parallel programming languages such as CUDA, OpenCL on CPUs, synchronization must be simulated correctly. The basic method is thread-based, which means all thread must execute one instruction in turn before execute the next one. In this paper, we propose function splitting to treat synchronization in a co routine style but not just thread-based. It splits the data-parallel function presented by low-level intermediate representation into several parts by simulating synchronization. We evaluate our method in translating PTX kernels to multi-core CPUs, the result of which shows this method could promotes performance by 15% compared to thread-based method. Our main contribution is a generous synchronization treatment that performs on low-level intermediate code given by a control flow graph in SSA form." @default.
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- W2023241094 date "2013-11-01" @default.
- W2023241094 modified "2023-10-18" @default.
- W2023241094 title "The Synchronization Treatment in Implementing Data-Parallel Programming Languages on CPUs" @default.
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- W2023241094 doi "https://doi.org/10.1109/hpcc.and.euc.2013.275" @default.
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