Cited By
View all- Guo JZhang LRomero Hung JLi CZhao JGuo M(2022)FPGA sharing in the cloud: a comprehensive analysisFrontiers of Computer Science10.1007/s11704-022-2127-017:5Online publication date: 24-Dec-2022
Optimizing Data Layout and System Configuration on FPGA-based Heterogeneous Platforms
Pages 1 - 8
Abstract
The most attractive feature of field-programmable gate arrays (FPGAs) is their configuration flexibility. However, if the configuration is performed manually, this flexibility places a heavy burden on system designers to choose among a vast number of configuration parameters and program transformations. In this paper, we improve the state-of-the-art with two main innovations: First, we apply compiler-automated transformations to the data layout and program statements to create streaming accesses. Such accesses are turned into streaming interfaces when the kernels are implemented in hardware, allowing the kernels to run efficiently. Second, we use two-step mixed integer programming to first minimize the execution time and then to minimize energy dissipation. Configuration parameters are chosen automatically, including several important ones omitted by existing models. Experimental results demonstrate significant performance gains and energy savings using these techniques.
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Published: 05 November 2018
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Cited By
View all- Guo JZhang LRomero Hung JLi CZhao JGuo M(2022)FPGA sharing in the cloud: a comprehensive analysisFrontiers of Computer Science10.1007/s11704-022-2127-017:5Online publication date: 24-Dec-2022