Defying the speed of light:: a spatially-aware compiler for wire-exposed architectures

Saman P. Amarasinghe
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Abstract

With the increasing miniaturization of transistors, wire delays are becoming a dominant factor in microprocessor performance. To address this issue, a number of emerging architectures contain replicated processing units with software-exposed communication between one unit and another (e.g., Raw, SmartMemories, TRIPS). However, for them to be effective, it is necessary to use languages that circumvent the von Neumann bottleneck, inherent in current programming languages such as C, C++ and Java.In the first part of the talk, I will introduce StreamIt, a streaming language that is ideally suited for wire-exposed architectures. StreamIt provides novel high-level representations to improve programmer productivity and program robustness within the streaming domain. At the same time, StreamIt exposes the inherent communication pattern of the program, allowing the compiler to aggressively optimize and effectively utilize wire-exposed architectures. .In the second part of the talk, I will describe our compiler from StreamIt to the Raw processor. Though StreamIt exposes the parallelism and communication patterns of stream programs, much analysis is needed to adapt a stream program to a wire-exposed processor. These include fission and fusion transformations that is used to adjust the granularity of a stream graph, a layout algorithm for mapping a stream graph to a given network topology, and a scheduling algorithm for generating a fine-grained static communication pattern for each computational element.
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藐视光速::一个空间感知的编译器,适用于线路暴露的架构
随着晶体管的日益小型化,线延迟正成为影响微处理器性能的主要因素。为了解决这个问题,许多新兴的架构包含了复制的处理单元,并在一个单元和另一个单元之间进行软件暴露通信(例如,Raw, SmartMemories, TRIPS)。然而,为了使它们有效,有必要使用绕过冯诺依曼瓶颈的语言,这是当前编程语言(如C、c++和Java)固有的。在演讲的第一部分,我将介绍StreamIt,这是一种非常适合于线暴露架构的流媒体语言。StreamIt提供了新颖的高级表示,以提高程序员的工作效率和流领域内的程序健壮性。同时,StreamIt暴露了程序固有的通信模式,允许编译器积极地优化和有效地利用线暴露的架构。在演讲的第二部分,我将描述我们的编译器从StreamIt到Raw处理器。虽然StreamIt暴露了流程序的并行性和通信模式,但是需要进行大量的分析才能使流程序适应于有线公开的处理器。其中包括用于调整流图粒度的裂变和融合转换,用于将流图映射到给定网络拓扑的布局算法,以及用于为每个计算元素生成细粒度静态通信模式的调度算法。
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