负载切片核心微架构

Trevor E. Carlson, W. Heirman, O. Allam, S. Kaxiras, L. Eeckhout
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引用次数: 54

摘要

在暴露指令级并行性(ILP)的动机驱动下,微处理器内核已经从简单的有序管道演变为复杂的超标量无序设计。通过提取ILP,这些处理器还支持并行缓存和内存操作,这是一个有用的副作用。然而,今天,越来越多的片外内存墙和多核处理器复杂的缓存层次结构使得缓存和内存访问的成本越来越高。这增加了提取内存层次并行性(MHP)的重要性,同时减少了更通用但复杂且耗电的ilp提取技术的净影响。此外,对于在功率和能量受限的环境中运行的多核处理器,能效已经在很大程度上取代了单线程性能,成为主要关注的问题。基于这一观察,我们提出了一个核心微架构,其目标是在最大限度地提高能源效率的同时,直接生成对内存层次结构的并行访问。Load Slice内核扩展了高效的按顺序、停止使用的内核,采用了第二个按顺序管道,使内存访问和地址生成指令能够绕过主管道中的停止指令。包含导致加载和存储的地址生成指令的向后程序切片由硬件自动提取,使用一种新的迭代算法,不需要软件支持或重新编译。平均而言,负载切片核心在基准有序处理器的基础上提高了53%的性能,而面积开销仅为15%,功耗仅为22%,导致能源效率(MIPS/Watt)分别比有序和无序设计提高43%和4.7倍以上。此外,对于功耗和面积受限的多核设计,Load Slice Core的性能优于有序设计和无序设计,分别提高了53%和95%的性能,从而为未来的多核处理器提供了另一种方向。
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The Load Slice Core microarchitecture
Driven by the motivation to expose instruction-level parallelism (ILP), microprocessor cores have evolved from simple, in-order pipelines into complex, superscalar out-of-order designs. By extracting ILP, these processors also enable parallel cache and memory operations as a useful side-effect. Today, however, the growing off-chip memory wall and complex cache hierarchies of many-core processors make cache and memory accesses ever more costly. This increases the importance of extracting memory hierarchy parallelism (MHP), while reducing the net impact of more general, yet complex and power-hungry ILP-extraction techniques. In addition, for multi-core processors operating in power- and energy-constrained environments, energy-efficiency has largely replaced single-thread performance as the primary concern. Based on this observation, we propose a core microarchitecture that is aimed squarely at generating parallel accesses to the memory hierarchy while maximizing energy efficiency. The Load Slice Core extends the efficient in-order, stall-on-use core with a second in-order pipeline that enables memory accesses and address-generating instructions to bypass stalled instructions in the main pipeline. Backward program slices containing address-generating instructions leading up to loads and stores are extracted automatically by the hardware, using a novel iterative algorithm that requires no software support or recompilation. On average, the Load Slice Core improves performance over a baseline in-order processor by 53% with overheads of only 15% in area and 22% in power, leading to an increase in energy efficiency (MIPS/Watt) over in-order and out-of-order designs by 43% and over 4.7×, respectively. In addition, for a power- and area-constrained many-core design, the Load Slice Core outperforms both in-order and out-of-order designs, achieving a 53% and 95% higher performance, respectively, thus providing an alternative direction for future many-core processors.
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