Making domain-specific hardware synthesis tools cost-efficient

N. George, D. Novo, Tiark Rompf, Martin Odersky, P. Ienne
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引用次数: 23

Abstract

Tools to design hardware at a high level of abstraction promise software-like productivity for hardware designs. Among them, tools like Spiral, HDL Coder, Optimus and MMAlpha target specific application domains and produce highly efficient implementations from high-level input specifications in a Domain Specific Language (DSL). But, developing similar domain-specific High-Level Synthesis (HLS) tools need enormous effort, which might offset their many advantages. In this paper, we propose a novel, cost-effective approach to develop domain-specific HLS tools. We develop the HLS tool by embedding its input DSL in Scala and using Lightweight Modular Staging (LMS), a compiler framework written in Scala, to perform optimizations at different abstraction levels. For example, to optimize computation on matrices, some optimizations are more effective when the program is represented at the level of matrices while others are better applied at the level of individual matrix elements. To illustrate the proposed approach, we create an HLS flow to automatically generate efficient hardware implementations of matrix expressions described in our own high-level specification language. Although a simple example, it shows how easy it is to reuse modules across different HLS flows and to integrate our flow with existing tools like LegUp, a C-to-RTL compiler, and FloPoCo, an arithmetic core generator. The results reveal that our approach can simultaneously achieve high productivity and design quality with a very reasonable tool development effort.
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在高抽象层次上设计硬件的工具保证了硬件设计的类似软件的生产力。其中,像Spiral、HDL Coder、Optimus和MMAlpha这样的工具针对特定的应用领域,并通过领域特定语言(DSL)的高级输入规范生成高效的实现。但是,开发类似的特定于领域的高级综合(High-Level Synthesis, HLS)工具需要付出巨大的努力,这可能会抵消它们的许多优点。在本文中,我们提出了一种新颖的、经济有效的方法来开发特定领域的HLS工具。我们将HLS工具的输入DSL嵌入到Scala中,并使用轻量级模块化分期(LMS)(一个用Scala编写的编译器框架)在不同的抽象级别执行优化,从而开发出HLS工具。例如,为了优化矩阵上的计算,当程序在矩阵级别上表示时,一些优化更有效,而另一些优化则在单个矩阵元素级别上更好地应用。为了说明所提出的方法,我们创建了一个HLS流来自动生成用我们自己的高级规范语言描述的矩阵表达式的高效硬件实现。虽然是一个简单的示例,但它显示了跨不同HLS流重用模块以及将我们的流与现有工具(如LegUp (C-to-RTL编译器)和FloPoCo(算术核心生成器)集成是多么容易。结果表明,我们的方法可以同时实现高生产力和设计质量与一个非常合理的工具开发工作。
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