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Shrink-Fit: A Framework for Flexible Accelerator Sizing

机译:收缩配合:灵活的加速器尺寸调整框架

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RTL design complexity discouraged adoption of reconfigurable logic in general purpose systems, impeding opportunities for performance and energy improvements. Recent improvements to HLS compilers simplify RTL design and are easing this barrier. A new challenge will emerge: managing reconfigurable resources between multiple applications with custom hardware designs. In this paper, we propose a method to "shrink-fit" accelerators within widely varying fabric budgets. Shrink-fit automatically shrinks existing accelerator designs within small fabric budgets and grows designs to increase performance when larger budgets are available. Our method takes advantage of current accelerator design techniques and introduces a novel architectural approach based on fine-grained virtualization. We evaluate shrink-fit using a synthesized implementation of an IDCT for decoding JPEGs and show the IDCT accelerator can shrink by a factor of 16x with minimal performance and area overheads. Using shrink-fit, application designers can achieve the benefits of hardware acceleration with single RTL designs on FPGAs large and small.
机译:RTL设计的复杂性不鼓励在通用系统中采用可重新配置的逻辑,从而阻碍了性能和能源改进的机会。 HLS编译器的最新改进简化了RTL设计,并缓解了这一障碍。一个新的挑战将出现:使用自定义硬件设计管理多个应用程序之间的可重新配置资源。在本文中,我们提出了一种在各种面料预算范围内“收缩配合”促进剂的方法。收缩配合可在较小的织物预算内自动收缩现有的加速器设计,并在可用大量预算时扩展设计以提高性能。我们的方法利用了当前的加速器设计技术,并引入了一种基于细粒度虚拟化的新颖架构方法。我们使用IDCT的综合实现对JPEG进行解码来评估收缩配合,并显示IDCT加速器可以收缩16倍,而性能和面积开销却最小。使用收缩配合,应用设计人员可以通过大小不同的FPGA上的单个RTL设计来获得硬件加速的好处。

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