一种向分支指令后插入冗余指令的容错微结构

随着深亚微米工艺的广泛应用,瞬态故障已成为芯片失效的主要原因.文中提出了一种向分支指令后插入冗余指令的容错微结构,利用分支误预测浪费的处理带宽,降低了冗余执行导致的性能损失.实验结果表明,该技术的性能损失在6%～31%之间,平均为21%,明显低于MBI技术而和DIE技术的性能损失相当.该技术能够检测流水线上各阶段发生的瞬态故障并能恢复处理器状态,故障检测延时短,需要的硬件开销也较小,非常适合提高带有简单预测机制的嵌入式微处理器的容错能力.     

通过两个取指令部件消除流水线控制相关延迟

分支预测技术能够在一定程序上消除指令间的控制相关延迟，提高微处理器的性能，是微处理器设计的一项关键技术，一般说来，静态分支预测效率低，动态分支预测硬件复杂度高，嵌入式微处理器具有功耗低、硬件复杂度低等特点，这决定了它必须采用特殊的分支处理技术，本文提出了一种面向嵌入式微处理器的分支处理技术，利用双端口指 指令Cache,加上预期指令，在编译器的共同配合下，消除由控制相关引起的延迟，模拟结果表明，该技术具有硬件复杂度低，实现简单、控制相关消除率高等优点。     

安腾处理器中多级分支预测机制

分支预测技术可消除分支指令之后损失的周期,防止流水线断流。高比率的分支预测精确度是高性能微处理器性能的保证。本文详细分析了安腾处理器(Itanium)多级分支预测机制,并研究了每级预测器的具体实现。     

安腾处理器中多级分支预测机制

分支预测技术可消除分支指令之后损失的周期,防止流水线断流.高比率的分支预测精确度是高性能微处理器性能的保证.本文详细分析了安腾处理器(Itanium)多级分支预测机制,并研究了每级预测器的具体实现.     

一种基于汇编代码的单重循环向量化方法

1 引言在微处理器设计中,开发指令级并行(ILP)以提高微处理器系统的性能受到了很大的限制。研究更大发射的超标量微处理器已经是一件极其复杂而没有意义的事。但是如果在开发指令级并行的同时,开发数据级并行,理论分析表明可以显著提高微处理器的性能,微处理器的等效IPC(每个时钟周期发射的指令条数)和超标量微处理器相比可以提高20～40多倍。因此,在微处理器系统设计中开发数据级并行具有重要的理论意义和实用价值。     

基于同时多线程的IFSBSMT取指策略研究

取指策略直接影响处理器的指令吞吐率.针对传统处理器取指策略存在取指带宽利用不均衡、指令队列冲突率高的缺点,提出基于同时多线程处理器的取指策略IFSBSMT.该策略以线程的IPC值为基础,速取优先级高的线程进行取指,并利用预取指令条数预算的方式分配取指带宽,采取线程IPC值和L2 Cache缺失率的双优先级动态资源分配机制分配处理器的系统资源.研究结果表明,IFSBSMT策略有效地解决了取指带宽、指令队列冲突及资源浪费问题,进一步提高了指令吞吐率,且具有较好的取指公平性.     

基于指令距离的存储相关性预测方法

存储相关性预测对于减少存储相关性冲突、提高微处理器性能具有十分重要的作用。针对传统相关性预测器硬件开销大、可实现性较差的缺点,通过对存储相关性的局部性分析,提出了一种基于指令距离的存储相关性预测方法。该方法充分利用了发生存储相关性冲突的指令在指令距离上的局部性,预测冲突指令的指令距离,进而控制部分访存指令的发射时机,大大减少了存储相关性冲突的次数。实验结果表明,在硬件开销约为1KB的情况下,使用基于指令距离的相关性预测器后,每个时钟周期平均执行的指令数可以提高1.70%,最高可以提高5.11%。在硬件开销较小的情况下,较大程度提高了微处理器的性能。     

同时多线程处理器上的动态分支预测器设计方案研究

同时多线程处理器（SMT）每个周期能够从多个线程中发射指令执行，从而大大地提高了超标量微处理器的指令吞吐量，但多个线程的同时执行也带来了许多硬件资源的共享冲突问题.其中，多个线程共享分支预测硬件的方案会对分支预测精度产生较大的影响.研究SMT处理器中分支处理方案对于处理器整体性能的影响，对于指导SMT处理器的设计是十分重要的.本文利用SMT处理器模拟器，针对各线程运行独立应用的SMT结构实验评估了几种著名的分支预测方案;给出了在单线程和多线程情况下，分支预测方案对分支预测精度和处理器整体性能的影响的分析;总结出在这样的SMT结构中，各线程拥有独立的预测器是一种较好的选择，并且由于各独立预测器可以采用小而简单的结构，所以不会带来太多的硬件开销.     

嵌入式微处理器分支预测的设计与实现

针对五级流水线嵌入式微处理器的特定应用环境,对分支预测技术进行了深入研究,提出了一种新的分支预测方案。该方案兼容带缓存设计,通过扩展指令总线,在取指段提前对分支指令跳转方向和目标地址进行预测,保存可能执行而未执行的指令和地址指针以备分支预测失效时得以恢复,减少了预测失效的代价,同时保证了指令流的正确执行。研究表明,该方案硬件开销小,预测效率高,预测失效代价低。     

一种基于VLIW结构的高性能变长指令发射机制

指令压缩技术能够克服传统超长指令字(very long instruction word,VLIW)结构的指令高速缓冲(cache)中长指令字密度低的缺陷,使长指令字中的各条指令能紧密地排列在高速缓冲行(cache line)中,但可能导致长指令字分置于两个cache line,使其不能同时参与取指与发射,从而成为处理器的性能瓶颈.受到分置cache line的影响,传统提升循环效率的软件流水方法性能下降.高性能变长指令发射窗的机制能够解决分离指令字带来的取指发射问题,为取指流水线提供高效连续的指令流,特别地,该机制缓存循环的一次迭代,硬件支持循环的软件流水,有效地增强VLIW结构的数字信号处理器(digital signal processor,DSP)的性能.通过搭建时钟精确的处理器仿真模型,并基于DSP/IMG库上进行仿真,结果显示,采用两级指令发射窗机制,平均性能提高约21.89％.     

An Exploration of Instruction Fetch Requirement in Out-of-Order Superscalar Processors

The performance of superscalar processors depends on many parameters with correlated effects. This paper explores the relations between some of these parameters, and more particularly, the requirement in instruction fetch bandwidth. We introduce new enhancements to increase the bandwidth of conventional instruction fetch engines. However, experiments show that the performance does not increase proportionally to the fetch. Once the measured IPC is half the instruction fetch bandwidth, increasing the fetch bandwidth brings very little improvement. In order to better understand this behavior, we develop a model from the empirical observation that the available instruction parallelism grows as the square root of the instruction window size. From the model, we derive that the fetch bandwidth requirement grows as the square root of the distance between mispredicted branches. We also verify experimentally that, to double the IPC, one should both double the fetch bandwidth and decrease the number of mispredicted branches fourfold.     

一种有效的同时多线程处理器取指控制机制

同时多线程处理器通过每时钟周期从多个运行的线程取指令执行,极大地提高了处理器的性能.分支预测器的预测精度和取指策略的效率是影响同时多线程处理器性能的关键.通过将一个基于值的分支预测器和一个基于线程推进速度的取指策略相结合,提出一种新的取指控制机制.该结构的硬件开销较小,实现复杂度较低.实验结果表明,该取指控制机制有效地提高了处理器的性能,其相对于传统取指控制机制的性能加速比为28%且该加速比也高于目前基于流缓冲区和基于分支分类器的取指控制机制.     

Modeling Control Speculation for Timing Analysis

The schedulability analysis of real-time embedded systems requires worst case execution time (WCET) analysis for the individual tasks. Bounding WCET involves not only language-level program path analysis, but also modeling the performance impact of complex micro-architectural features present in modern processors. In this paper, we statically analyze the execution time of embedded software on processors with speculative execution. The speculation of conditional branch outcomes (branch prediction) significantly improves a program's execution time. Thus, accurate modeling of control speculation is important for calculating tight WCET estimates. We present a parameterized framework to model the different branch prediction schemes. We further consider the complex interaction between speculative execution and instruction cache performance, that is, the fact that speculatively executed blocks can generate additional cache hits/misses. We extend our modeling to capture this effect of branch prediction on cache performance. Starting with the control flow graph of a program, our technique uses integer linear programming to estimate the program's WCET. The accuracy of our method is demonstrated by tight estimates obtained on realistic benchmarks.     

Scalability aspects of instruction distribution algorithms for clustered processors

In the evolving submicron technology, making it particularly attractive to use decentralized designs. A common form of decentralization adopted in processors is to partition the execution core into multiple clusters. Each cluster has a small instruction window, and a set of functional units. A number of algorithms have been proposed for distributing instructions among the clusters. The first part of this paper analyzes (qualitatively as well as quantitatively) the effect of various hardware parameters such as the type of cluster interconnect, the fetch size, the cluster issue width, the cluster window size, and the number of clusters on the performance of different instruction distribution algorithms. The study shows that the relative performance of the algorithms is very sensitive to these hardware parameters and that the algorithms that perform relatively better with four or fewer clusters are generally not the best ones for a larger number of clusters. This is important, given that with an imminent increase in the transistor budget, more clusters are expected to be integrated on a single chip. The second part of the paper investigates alternate interconnects that provide scalable performance as the number of clusters is increased. In particular, it investigates two hierarchical interconnects - a single ring of crossbars and multiple rings of crossbars - as well as instruction distribution algorithms to take advantage of these interconnects. Our study shows that these new interconnects with the appropriate distribution techniques achieve an IPC (instructions per cycle) that is 15-20 percent better than the most scalable existing configuration, and is within 2 percent of that achieved by a hypothetical ideal processor having a 1-cycle latency crossbar interconnect. These results confirm the utility and applicability of hierarchical interconnects and hierarchical distribution algorithms in clustered processors.     

Software Trace Cache for Commercial Applications

In this paper we address the important problem of instruction fetch for future wide issue superscalar processors. Our approach focuses on understanding the interaction between software and hardware techniques targeting an increase in the instruction fetch bandwidth. That is the objective, for instance, of the Hardware Trace Cache (HTC). We design a profile based code reordering technique which targets a maximization of the sequentiality of instructions, while still trying to minimize instruction cache misses. We call our software approach, Software Trace Cache (STC). We evaluate our software approach, and then compare it with the HTC and the combination of both techniques. Our results on PostgreSQL show that for large codes with few loops and deterministic execution sequences the STC offers better results than a HTC. Also, both the software and hardware approaches combine well to obtain improved results.     

Using conditional execution to exploit instruction level concurrency

Multiple-instruction-issue processors seek to improve performance over scalar RISC processors by providing multiple pipelined functional units in order to fetch, decode and execute several instructions per cycle. The process of identifying instructions which can be executed in parallel and distributing them between the available functional units is referred to as instruction scheduling. This paper describes a simple compile-time scheduling technique, called conditional compaction, which uses the concept of conditional execution to move instructions across basic block boundaries. It then presents the results of an investigation into the performance of the scheduling technique using C benchmark programs scheduled for machines with different functional unit configurations. This paper represents the culmination of our investigation into how much performance improvement can be obtained using conditional execution as the sole scheduling technique.     

One billion transistors, one uniprocessor, one chip

Billion-transistor processors will be much as they are today, just bigger, faster and wider (issuing more instructions at once). The authors describe the key problems (instruction supply, data memory supply and an implementable execution core) that prevent current superscalar computers from scaling up to 16- or 32-instructions per issue. They propose using out-of-order fetching, multi-hybrid branch predictors and trace caches to improve the instruction supply. They predict that replicated first-level caches, huge on-chip caches and data value speculation will enhance the data supply. To provide a high-speed, implementable execution core that is capable of sustaining the necessary instruction throughput, they advocate a large, out-of-order-issue instruction window (2,000 instructions), clustered (separated) banks of functional units and hierarchical scheduling of ready instructions. They contend that the current uniprocessor model can provide sufficient performance and use a billion transistors effectively without changing the programming model or discarding software compatibility     

Increasing the Instruction Fetch Rate via Block-Structured Instruction Set Architectures

To exploit larger amounts of instruction level parallelism, processors are being built with wider issue widths and larger numbers of functional units. Instruction fetch rate must also be increased in order to effectively exploit the performance potential of such processors. Block-structured ISAs provide an effective means of increasing the instruction fetch rate. We define an optimization, called block enlargement, that can be applied to a block-structured ISA to increase the instruction fetch rate of a processor that implements that ISA. We have constructed a compiler that generates block-structured ISA code, and a simulator that models the execution of that code on a block-structured ISA processor. We show that for the SPECint95 benchmarks, the block-structured ISA improves the performance of an aggressive wide issue, dynamically scheduled processor by 15% while using simpler microarchitectural mechanisms to support wide issue and dynamic scheduling.     

基于预取和缓存原理的片上Flash加速控制器设计

为了提高片上Flash在嵌入式应用中的读取速度,提出了一种基于预取和缓存原理的片上Flash加速控制器。该控制器包括预取缓存和高速缓存两种加速方案。其中预取缓存方案采用位宽扩展和预取技术加速顺序指令的读取,并采用分支缓存存储非顺序指令,降低由非顺序指令造成的预取缺失代价;而高速缓存方案采用组相联和路预测技术,提高指令重用率,减少Flash访问次数,降低系统功耗。针对不同的应用场景,两种加速方案既可通过寄存器来静态切换,也可通过软件流程来自适应动态切换,从而获得最佳的读取速度提升。多项基准程序的测试结果表明了所提出的片上Flash加速控制器在性能和功耗优化上的可行性和高效性。     

一种具有QoS特性的同时多线程处理器取指策略

同时多线程处理器通过每时钟周期从多个运行的线程取指令执行，从而极大地提高了处理器的性能．建议了一种具有QoS特性的同时多线程处理器取指策略，并讨论了其在QoS管理方面的问题．该策略的核心思想是利用线程的优先级和流速来同时控制线程的取指过程，从而满足线程在执行速度上的QoS需求．与传统的基于纯优先级的取指策略相比，该策略不但具有QoS特性，同时还可以更加有效地分配取指带宽，从而能获得更高的处理器性能．该策略的物理实现非常简单．模拟实验的结果表明，该策略在提供Qos支持的基础上，可以在传统的基于优先级的取指策略ICOUNT的基础上提高15％的系统性能．