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Exploiting choice

Dean M. Tullsen, Susan J. Eggers, Joel Emer, Henry M. Levy, Jack Lo, Rebecca L. Stamm

Open publisher page 781 citations

Abstract

Simultaneous multithreading is a technique that permits multiple independent threads to issue multiple instructions each cycle. In previous work we demonstrated the performance potential of simultaneous multithreading, based on a somewhat idealized model. In this paper we show that the throughput gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact on the conventional superscalar design, (2) it has minimal performance impact on a single thread executing alone, and (3) it achieves significant throughput gains when running multiple threads. Our simultaneous multithreading architecture achieves a throughput of 5.4 instructions per cycle, a 2.5-fold improvement over an unmodified superscalar with similar hardware resources. This speedup is enhanced by an advantage of multithreading previously unexploited in other architectures: the ability to favor for fetch and issue those threads most efficiently using the processor each cycle, thereby providing the "best" instructions to the processor.

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What this paper is about

Simultaneous multithreading is a technique that permits multiple independent threads to issue multiple instructions each cycle. In previous work we demonstrated the performance potential of simultaneous multithreading, based on a somewhat idealized model. In this paper we show that the throughput gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact on the conventional superscalar design, (2) it has minimal performance impact on a single thread executing alone, and (3) it achieves significant throughput gains when running multiple threads. Our simultaneous multithreading architecture achieves a throughput of 5.4 instructions per cycle, a 2.5-fold improvement over an unmodified superscalar with similar hardware resources. This speedup is enhanced by an advantage of multithreading previously unexploited in other architectures: the ability to favor for fetch and issue those threads most efficiently using the processor each cycle, thereby providing the "best" instructions to the processor.

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Available abstract

Simultaneous multithreading is a technique that permits multiple independent threads to issue multiple instructions each cycle. In previous work we demonstrated the performance potential of simultaneous multithreading, based on a somewhat idealized model. In this paper we show that the throughput gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact on the conventional superscalar design, (2) it has minimal performance impact on a single thread executing alone, and (3) it achieves significant throughput gains when running multiple threads. Our simultaneous multithreading architecture achieves a throughput of 5.4 instructions per cycle, a 2.5-fold improvement over an unmodified superscalar with similar hardware resources. This speedup is enhanced by an advantage of multithreading previously unexploited in other architectures: the ability to favor for fetch and issue those threads most efficiently using the processor each cycle, thereby providing the "best" instructions to the processor.

Key concepts: Multithreading, Simultaneous multithreading, Computer science, Thread (computing), Parallel computing, Speedup, Throughput, Yarn

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