异构计算中的任务调度和内存管理

Amit Jindal, Wenjia Ruan
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引用次数: 2

摘要

任务调度和内存管理是使异构计算难以普及的难题。有几种编程模型和工具针对CPU和GPU之间的工作负载分区和数据可访问性。我们已经开发并部署了Symphony SDK,这是一个框架,它使工作负载分区、调度和内存管理对开发人员来说变得“简单”。在这次演讲中,我们将介绍Symphony架构,详细说明现有的OpenCL内核如何与Symphony的异构任务同步、任务调度和内存管理功能一起重用。我们还将分享Symphony提供2 -6倍性能加速的实际案例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Symphony: Task Scheduling and Memory Management in Heterogeneous Computing
Task scheduling and memory management are challenges that make Heterogeneous Computing difficult for the masses. There are several programming models and tools that exist targeting partitioning of workload and accessibility of data between CPU and GPU. We have developed and deployed Symphony SDK - a framework that makes workload partitioning, scheduling and memory management 'simple' for developers. In this talk, we will introduce Symphony architecture, elaborate how existing OpenCL kernels can be reused with heterogeneous task synchronization, task scheduling, and memory management capabilities of Symphony. We will also share real-world cases where Symphony has provided 2x-6x performance speed-ups.
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