Unlocking FPGAs Using High Level Synthesis Compiler Technologies

F. Martinez-Vallina, Henry Styles
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Abstract

FPGA devices have long been the standard for massively parallel computing fabrics with a low power footprint. Unfortunately, the complexity associated with an FPGA design has limited the rate of adoption by software application programmers. Recent advances in compiler and FPGA fabric capabilities are reversing this trend and there is a growing adoption of FPGAs for algorithmic workloads such as data analytics, feature detection in images, adaptive beam forming, etc. One of the pillars of this shift is the Vivado HLS compiler, which enables the compilation of algorithms captured in C and C++into efficient FPGA implementations. This talk focuses on how the HLS compiler creates algorithm specific compute architectures and how these elements are then used in an OpenCL based system level design abstraction. The evolution of these hardware design abstractions into software centric specifications enable application developers to leverage the flexibility of the FPGA fabric without the constraints typically found in fixed parallel architectures such as multi-core CPUs/GPUs.
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使用高级合成编译器技术解锁fpga
FPGA设备长期以来一直是具有低功耗的大规模并行计算结构的标准。不幸的是,FPGA设计的复杂性限制了软件应用程序程序员的采用率。编译器和FPGA结构能力的最新进展正在扭转这一趋势,越来越多的FPGA应用于算法工作负载,如数据分析、图像特征检测、自适应波束形成等。这种转变的支柱之一是Vivado HLS编译器,它可以将C和c++中捕获的算法编译成高效的FPGA实现。这次演讲的重点是HLS编译器如何创建特定算法的计算架构,以及这些元素如何在基于OpenCL的系统级设计抽象中使用。这些硬件设计抽象演变为以软件为中心的规范,使应用程序开发人员能够利用FPGA结构的灵活性,而不受固定并行架构(如多核cpu / gpu)中的典型约束。
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