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The ARISE Approach for Extending Embedded Processors With Arbitrary Hardware Accelerators

机译:利用任意硬件加速器扩展嵌入式处理器的ARISE方法

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ARISE introduces a systematic approach for extending once an embedded processor to support thereafter the coupling of an arbitrary number of custom computing units (CCUs). A CCU can be a hardwired or a reconfigurable unit, which can be utilized following a tight and/or loose model of computation. By selecting the appropriate model of computation for each part of the application, the complete application space is considered for acceleration, resulting in significant performance improvements. Also, ARISE offers modularity and scalability and is not restricted by the opcode space and operands limitation problems that exist in such type of machines. To support these features we introduce a machine organization that allows the cooperation of a processor and a set of CCUs. To control the CCUs we extend once the instruction set of the processor with eight instructions. To efficiently incorporate these features to an embedded processor, we propose a micro-architecture implementation that minimizes the control and communication overhead between the processor and the CCUs. To evaluate our proposal, we extended a MIPS processor with the ARISE infrastructure and implemented it on a Xilinx field-programmable gate array (FPGA). Implementation results, demonstrate that the timing model of the processor is not affected. Also, we implemented a set of benchmarks on the ARISE evaluation machine. Performance results prove significant improvements and reduced communication overhead compared to a typical coprocessor approach.
机译:ARISE引入了一种系统的方法,可将嵌入式处理器扩展一次,以支持此后任意数量的定制计算单元(CCU)的耦合。 CCU可以是硬连线的或可重新配置的单元,可以按照严格和/或宽松的计算模型来使用。通过为应用程序的每个部分选择适当的计算模型,可以考虑整个应用程序空间来加速,从而显着提高性能。而且,ARISE提供了模块化和可伸缩性,并且不受此类机器中存在的操作码空间和操作数限制问题的限制。为了支持这些功能,我们引入了一种机器组织,该组织允许处理器和一组CCU的协作。为了控制CCU,我们将处理器的指令集扩展为8条指令。为了将这些功能有效地集成到嵌入式处理器中,我们提出了一种微体系结构实现,该实现可最大程度地减少处理器与CCU之间的控制和通信开销。为了评估我们的建议,我们使用ARISE基础架构扩展了MIPS处理器,并在Xilinx现场可编程门阵列(FPGA)上实现了它。实现结果表明,处理器的时序模型不受影响。此外,我们在ARISE评估机上实施了一组基准测试。与典型的协处理器方法相比,性能结果证明了显着的改进并减少了通信开销。

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