The performance tradeoff between hardware complexity and clock speed is studied. First, a generic superscalar pipeline is defined. Then the specific areas of register renaming, instruction window wakeup and selection logic, and operand bypassing are analyzed. Each is modeled and Spice simulated for feature sizes of 0:8 m, 0:35 m, and0:18 m. Performance results and trends are expressed in terms of issue width and window size. Our analysis indicates that window wakeup and selection logic as well as operand bypass logic are likely to be the most critical in the future. A microarchitecture that simplifies wakeup and selection logic is proposed and discussed. This implementation puts chains of dependent instructions into queues, and issues instructions from multiple queues in parallel. Simulation shows little slowdown as compared with a completely flexible issue window when performance is measured in clock cycles. Furthermore, because only instructions at queue heads need to be awakened and selected, issue logic is simplified and the clock cycle is faster – consequently overall performance is improved. By grouping dependent instructions together, the proposed microarchitecture will help minimize performance degradation due to slow bypasses in future wide-issue machines. 1

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For maximum performance, an out-of-order processor must issue load instructions as early as possible, while avoiding memory-order violations with prior store instructions that write to the same memory location. One approach is to use memory dependence prediction to identify the stores upon which a load depends, and communicate that information to the instruction scheduler. We designate the set of stores upon which each load has depended as the load's "store set". The processor can dis- cover and use a load's store set to accurately predict the earliest time the load can safely execute. We show that store sets accurately predict memory dependencies in the context of large instruction window, superscalar machines, and allow for near-optimal performance compared to an instruction scheduler with perfect knowledge of memory dependencies. In addition, we explore the implementation aspects of store sets, and describe a low cost implementation that achieves nearly optimal performance.

Dependences among loads and stores whose addresses are unknown hinder the extraction of instruction level parallelism during the execution of a sequential program. Such ambiguous memory dependences can be overcome by memory dependence speculation which enables a load or store to be speculatively executed before the addresses of all preceding loads and stores are known. Furthermore, multiple speculative stores to a memory location create multiple speculative versions of the location. Program order among the speculative versions must be tracked to maintain sequential semantics. A previously proposed approach, the Address Resolution Buffer(ARB) uses a centralized buffer to support speculative versions. Our proposal, called the Speculative Versioning Cache(SVC), uses distributed caches to eliminate the latency and bandwidth problems of the ARB. The SVC conceptually unifies cache coherence and speculative versioning by using an organization similar to snooping bus-based coherent caches. A preliminary evaluation for the Multiscalar architecture shows that hit latency is an important factor affecting performance, and private cache solutions trade-off hit rate for hit latency. 1.

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We introduce a dynamic scheme that captures the access patterns of linked data structures and can be used to predict future accesses with high accuracy. Our technique exploits the dependence relationships that exist between loads that produce addresses and loads that consume these addresses. By identifying producer-consumer pairs, we construct a compact internal representation for the associated structure and its traversal. To achieve a prefetching effect, a small prefetch engine speculatively traverses this representation ahead of the executing program. Dependence-based prefetching achieves speedups of up to 25% on a suite of pointer-intensive programs. 1 Introduction Linked data structures (LDS) such as lists and trees are used in many important applications. The importance of LDS is growing with the increasing popularity of C++, Java, and other systems that use linked object graphs and function tables. Flexible, dynamic construction allows linked structures to grow large and diffic...

Keywords: Chip-multiprocessor, speculative multithreading, data-dependence speculation, control speculation \Lambda Corresponding Author 1 1 INTRODUCTION The superscalar approach [12], which allows more than one instruction to be issued in a single cycle, has become the norm for today's high-performance microprocessors. The issue rate of these microprocessors has continued to increase over the past few years, with today's high-performance superscalar processors such as the Compaq Alpha 21264 [4], IBM PowerPC [16], Intel Pentium-Pro [3] or MIPS R10000 [19] able to issue up to four instructions per cycle.

As processors continue to exploit more instruction level parallelism, a greater demand is placed on reducing the effects of memory access latency. In this paper, we introduce a novel modification of the processor pipeline called memory renaming. Memory renaming applies register access techniques to load instructions, reducing the effect of delays caused by the need to calculate effective addresses for the load and all preceding stores before the data can be fetched. Memory renaming allows the processor to speculatively fetch values when the producer of the data can be reliably determined without the need for an effective address. This work extends previous studies of data value and dependence speculation. When memory renaming is added to the processor pipeline, renaming can be applied to 30% to 50% of all memory references, translating to an overall improvement in execution time of up to 41%. Furthermore, this improvement is seen across all memory segments -- including the heap segment...

We revisit memory hierarchy design viewing memory as an inter-operation communication agent. This perspective leads to the development of novel methods of performing inter-operation memory communication: (1) We use data dependence prediction to identify and link dependent loads and stores so that they can communicate speculatively without incurring the overhead of address calculation, disambiguation and data cache access. (2) We also use data dependence prediction to convert, DEFstore-load-USE chains within the instruction window into DEF-USE chains prior to address calculation and disambiguation. (3) We use true and output data dependence status prediction to introduce and manage a small storage structure called the Transient Value Cache (TVC). The TVC captures memory values that are short-lived. It also captures recently stored values that are likely to be accessed soon. Accesses that are serviced by the TVC do not have to be serviced by other parts of the memory hierarchy, e.g., the data cache. The first two techniques are aimed at reducing the effective communication latency whereas the last technique is aimed at reducing data cache bandwidth requirements. Experimental analysis of the proposed techniques shows that: (i) the proposed speculative communication methods correctly handle a large fraction of memory dependences, and (ii) a large number of the loads and stores do not have to ever reach the data cache when the TVC is in place. 1

For many applications, branch mispredictions and cache misses limit a processor's performance to a level well below its peak instruction throughput. A small fraction of static instructions, whose behavior cannot be anticipated using current branch predictors and caches, contribute a large fraction of such performance degrading events. This paper analyzes the dynamic instruction stream leading up to these performance degrading instructions to identify the operations necessary to execute them early. The backward slice (the subset of the program that relates to the instruction) of these performance degrading instructions, if small compared to the whole dynamic instruction stream, can be pre-executed to hide the instruction's latency. To overcome conservative dependence assumptions that result in large slices, speculation can be used, resulting in speculative slices. This paper provides an initial characterization of the backward slices of L2 data cache misses and branch mispredictions, and shows the effectiveness of techniques, including memory dependence prediction and control independence, for reducing the size of these slices. Through the use of these techniques, many slices can be reduced to less than one tenth of the full dynamic instruction stream when considering the 512 instructions before the performance degrading instruction. 1