Node level heterogeneous architectures have become attractive during the last decade for several reasons: compared to traditional symmetric CPUs, they offer high peak performance and are energy and/or cost efficient. With the increase of fine-grained parallelism in high-performance computing, as well as the introduction of parallelism in workstations, there is an acute need for a good overview and understanding of these architectures. We give an overview of the state-of-the-art in heterogeneous computing, focusing on three commonly found architectures: the Cell Broadband Engine Architecture, graphics processing units (GPUs), and field programmable gate arrays (FPGAs). We present a review of hardware, available software tools, and an overview of state-of-the-art techniques and algorithms. Furthermore, we present a qualitative and quantitative comparison of the architectures, and give our view on the future of heterogeneous computing.

中文翻译：

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异构计算的最新技术

在过去的十年中，节点级异构体系结构吸引了人们，原因如下：与传统的对称CPU相比，它们具有较高的峰值性能，并且具有能源和/或成本效益。随着高性能计算中细粒度并行性的增加以及工作站中并行性的引入，迫切需要对这些体系结构有一个很好的了解和理解。我们概述了异构计算的最新技术，重点介绍了三种常见的体系结构：单元宽带引擎体系结构，图形处理单元（GPU）和现场可编程门阵列（FPGA）。我们对硬件，可用的软件工具进行了概述，并对最新技术和算法进行了概述。此外，