C-to-CoRAM: compiling perfect loop nests to the portable CoRAM abstraction

G. Weisz, J. Hoe
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引用次数: 5

Abstract

This paper presents initial work on developing a C compiler for the CoRAM FPGA computing abstraction. The presented effort focuses on compiling fixed-bound perfect loop nests that operate on large data sets in external DRAM. As required by the CoRAM abstraction, the compiler partitions source code into two separate implementation components: (1) hardware kernel pipelines to be mapped onto the reconfigurable logic fabric; and (2) control threads that express, in a C-like language, the sequencing and coordination of data transfers between the hardware kernels and external DRAM. The compiler performs optimizations to increase parallelism and use DRAM bandwidth efficiently. It can target different FPGA platforms that support the CoRAM abstraction, either natively in a future FPGA or in soft-logic on today's devices. The CoRAM abstraction provides a convenient high-level compilation target to simplify the task of design optimization and system generation. The compiler is evaluated using three test programs (matrix-matrix multiplication, k-nearest neighbor, and 2D convolution) on the Xilinx ML605 and the Altera DE4. Results show that our compiler is able to target the different platforms and effectively exploit their dissimilar capacities and features. Depending on the application, the compiler-generated implementations achieve performance ranging from a factor of 4 slower to a factor of 2 faster relative to hand-designed implementations, as measured on actual hardware.
C-to-CoRAM:编译完美的循环巢到可移植的CoRAM抽象
本文介绍了为CoRAM FPGA计算抽象开发C编译器的初步工作。本文的工作重点是编译固定边界的完美循环巢,这些循环巢可以在外部DRAM中的大型数据集上运行。根据CoRAM抽象的要求,编译器将源代码划分为两个独立的实现组件:(1)将硬件内核管道映射到可重构逻辑结构上;(2)控制线程,用类似c的语言表达硬件内核和外部DRAM之间数据传输的顺序和协调。编译器执行优化以增加并行性并有效地使用DRAM带宽。它可以针对支持CoRAM抽象的不同FPGA平台,无论是在未来的FPGA中还是在当今设备的软逻辑中。CoRAM抽象提供了方便的高级编译目标,简化了设计优化和系统生成的任务。在Xilinx ML605和Altera DE4上使用三个测试程序(矩阵-矩阵乘法、k近邻和2D卷积)对编译器进行评估。结果表明,我们的编译器能够针对不同的平台,并有效地利用其不同的能力和特性。根据应用程序的不同,与手工设计的实现相比,编译器生成的实现的性能从慢4倍到快2倍不等,这是在实际硬件上测量的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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