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A task-level superscalar microarchitecture for large scale chip multiprocessors

机译:大规模芯片多处理器的任务级超标量微体系结构

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The complexity of explicit parallel programming greatly limits programmers to achieve further performance gain in chip-multiprocessors (CMPs). To simplify software programming for large scale CMPs, we present a task-level superscalar microarchitecture which acts as the Control Processor (CP) of the Multi-Level Computing Architecture (MLCA), a novel multicore architecture especially targeted for embedded multimedia and streaming application systems. This task-level superscalar consists of a ten-stage task pipeline and exploits parallelism among tasks by hardware register renaming and out-of-order execution techniques, much in the same way a traditional superscalar processor exploits instruction-level parallelism. The experimental results show that our design can scale up to 256 processors while maintaing a relatively low resource overhead, finally achieving a much faster task dependency decode rate and naturally more notable performance speedup than the software runtime.
机译:显式并行编程的复杂性极大地限制了程序员在芯片多处理器(CMP)中获得进一步的性能提升。为了简化大规模CMP的软件编程,我们提出了一种任务级超标量微体系结构,它充当多级计算体系结构(MLCA)的控制处理器(CP),这是一种新颖的多核体系结构,特别针对嵌入式多媒体和流应用程序系统。该任务级超标量由十级任务流水线组成,通过硬件寄存器重命名和乱序执行技术来利用任务之间的并行性,与传统超标量处理器利用指令级并行性的方式非常相似。实验结果表明,我们的设计可以扩展到256个处理器,同时保持相对较低的资源开销,最终实现了比软件运行时更快的任务依赖解码速率,并且自然而然地提高了性能。

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