As the issue rate and depth of pipelining of high performance Superscalar processors increase, the importance of an excellent branch predictor becomes more vital to delivering the potential performance of a wide-issue, deep pipelined microarchitecture. We propose a new dynamic branch predictor (Two-Level Adaptive Branch Prediction) that achieves substantially higher accuracy than any other scheme reported in the literature. The mechanism uses twolevels of branch history information to make predictions, the history of the last k branches encountered, and the branch behavior for the last s occurrences of the speci c pattern of these k branches. We have identi ed three variations of the Two-Level Adaptive Branch Prediction, depending on how nely we resolve the history information gathered. We compute the hardware costs of implementing each of the three variations, and use these costs in evaluating their relative effectiveness. We measure the branch prediction accuracy of the three variations of Two-Level Adaptive Branch Prediction, along with several other popular proposed dynamic and static prediction schemes, on the SPEC benchmarks. We showthattheaverage prediction accuracy for Two-Level Adaptive Branch Prediction is 97 percent, while the other known schemes achieve at most 94.4 percent average prediction accuracy. We measure the e ectiveness of di erent prediction algorithms and di erent amounts of history and pattern information. We measure the costs of each variation to obtain the same prediction accuracy. 1

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The centerpiece of this thesis is a new processing paradigm for exploiting instruction level parallelism. This paradigm, called the multiscalar paradigm, splits the program into many smaller tasks, and exploits fine-grain parallelism by executing multiple, possibly (control and/or data) depen-dent tasks in parallel using multiple processing elements. Splitting the instruction stream at statically determined boundaries allows the compiler to pass substantial information about the tasks to the hardware. The processing paradigm can be viewed as extensions of the superscalar and multiprocess-ing paradigms, and shares a number of properties of the sequential processing model and the dataflow processing model. The multiscalar paradigm is easily realizable, and we describe an implementation of the multis-calar paradigm, called the multiscalar processor. The central idea here is to connect multiple sequen-tial processors, in a decoupled and decentralized manner, to achieve overall multiple issue. The mul-tiscalar processor supports speculative execution, allows arbitrary dynamic code motion (facilitated by an efficient hardware memory disambiguation mechanism), exploits communication localities, and does all of these with hardware that is fairly straightforward to build. Other desirable aspects of the

We propose a new processing paradigm, called the Expandable Split Window (ESW) paradigm, for exploiting finegrain parallelism. This paradigm considers a window of instructions (possibly having dependencies) as a single unit, and exploits fine-grain parallelism by overlapping the execution of multiple windows. The basic idea is to connect multiple sequential processors, in a decoupled and decentralized manner, to achieve overall multiple issue. This processing paradigm shares a number of properties of the restricted dataflow machines, but was derived from the sequential von Neumann architecture. We also present an implementation of the Expandable Split Window execution model, and preliminary performance results. 1. INTRODUCTION The execution of a program, in an abstract form, can be considered to be a dynamic dataflow graph that encapsulates the data dependencies in the program. The nodes of the graph represent computation operations, and the arcs of the graph represent communication o...

Improving the performance of C programs has been a topic of great interest for many years. Both hardware technology and compiler optimization research has been applied in an effort to make C programs execute faster. In many application domains, the C++ language is replacing C as the programming language of choice. In this paper, we measure the empirical behavior of a group of significant C and C++ programs and attempt to identify and quantify behavioral differences between them. Our goal is to determine whether optimization technology that has been successful for C programs will also be successful in C++ programs. We furthermore identify behavioral characteristics of C++ programs that suggest optimizations that should be applied in those programs. Our results show that C++ programs exhibit behavior that is significantly different than C programs. These results should be of interest to compiler writers and architecture designers who are designing systems to execute object-oriented programs.

Several researchers have proposed algorithms for basic block reordering. We call these branch alignment algorithms. The primary emphasis of these algorithms has been on improving instruction cache locality, and the few studies concerned with branch prediction reported small or minimal improvements. As wide-issue architectures become increasingly popular the importance of reducing branch costs will increase, and branch alignment is one mechanism which can effectively reduce these costs. In this paper, we propose an improved branch alignment algorithm that takes into consideration the architectural cost model and the branch prediction architecture when performing the basic block reordering. We show that branch alignment algorithms can improve a broad range of static and dynamicbranch prediction architectures. We also show that a programs performance can be improved by approximately 5% even whenusing recently proposed,highly accurate branch prediction architectures. The programs are compi...

As the issue rate and pipeline depth of high performance superscalar processors increase, the amount of speculative work issued also increases. Because speculative work must be thrown away in the event of a branch misprediction, wide-issue, deeply pipelined processors must employ accurate branch predictors to effectively exploit their performance potential. Many existing branch prediction schemes are capable of accurately predicting the direction of conditional branches. However, these schemes are ineffective in predicting the targets of indirect jumps achieving, on average, a prediction accuracy rate of 51.8% for the SPECint95 benchmarks. In this paper, we propose a new prediction mechanism, the target cache, for predicting indirect jump targets. For the perl and gcc benchmarks, this mechanism reduces the indirect jump misprediction rate by 93.4% and 63.3% and the overall execution time by 14% and 5%. 1 Introduction As the issue rate and pipeline depth of high performance superscala...

Superscalar processing is the latest in a long series of innovations aimed at producing ever-faster microprocessors. By exploiting instruction-level parallelism, superscalar processors are capable of executing more than one instruction in a clock cycle. This paper discusses the microarchitecture of superscalar processors. We begin with a discussion of the general problem solved by superscalar processors: converting an ostensibly sequential program into a more parallel one. The principles underlying this process, and the constraints that must be met, are discussed. The paper then provides a description of the specific implementation techniques used in the important phases of superscalar processing. The major phases include: i) instruction fetching and conditional branch processing, ii) the determination of data dependences involving register values, iii) the initiation, or issuing, of instructions for parallel execution, iv) the communication of data values through memory via loads and stores, and v) committing the process state in correct order so that precise interrupts can be supported. Examples of recent superscalar microprocessors, the MIPS R10000, the DEC 21164, and the AMD K5 are used to illustrate a variety of superscalar methods.

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A superscalar processor supporting speculative execution requires an instruction fetch mechanism that can provide instruction fetch addresses as nearly correct as possible and as soon as possible in order to reduce the likelihood of throwing away speculative work. In this paper we propose a comprehensive instruction fetch mechanism to satisfy that need. Implementation issues are identified, possible solutions and designs for resolving those issues are simulated, and the results of these simulations are presented. A metric for measuring the average penalty of executing a branch instruction is introduced and used to evaluate the performance of our instruction fetch mechanism. We achieve an average performance of 4.19 IPC on the original SPEC benchmarks in a machine which can execute ve instructions ideally by using the proposed mechanism.