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PipeRench: A Coprocessor for Streaming Multimedia Acceleration

机译:PipeRench:用于流媒体加速的协处理器

摘要

Future computing workloads will emphasize an architectureu27s ability to perform relatively simple calculations on massive quantities of mixed-width data. This paper describes a novel reconfigurable fabric architecture, PipeRench, optimized to accelerate these types of computations. PipeRench enables fast, robust compilers, supports forward compatibility, and virtualizes configurations, thus removing the fixed size constraint present in other fabrics. For the first time we explore how the bit-width of processing elements affects performance and show how the PipeRench architecture has been optimized to balance the needs of the compiler against the realities of silicon. Finally, we demonstrate extreme performance speedup on certain computing kernels (up to 190x versus a modern RISC processor), and analyze how this acceleration translates to application speedup.
机译:未来的计算工作负载将强调架构对大量混合宽度数据执行相对简单计算的能力。本文介绍了一种新颖的可重新配置结构体系结构PipeRench,该体系结构经过优化可加速这些类型的计算。 PipeRench支持快速,强大的编译器,支持前向兼容性,并虚拟化配置,从而消除了其他结构中存在的固定大小约束。第一次,我们探讨处理元素的位宽如何影响性能,并展示如何优化PipeRench架构,以平衡编译器的需求和芯片的实际情况。最后,我们演示了在某些计算内核上的最高性能提速(与现代RISC处理器相比,达到190倍),并分析了这种提速如何转化为应用程序提速。

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