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Inter-actions parallel execution on GPU from high-level dataflow synthesis
Publications associées (84)
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Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...
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Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...
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The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...
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Timely insights lead to business growth and scientific breakthroughs but require analytical engines that cope with the ever-increasing data processing needs. Analytical engines relied on rapid CPU improvements, yet the end of Dennard scaling stopped the fr ...
EPFL2022Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms
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The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...
2022