Proceedings ArticleDOI
Automatically characterizing large scale program behavior
Timothy Sherwood,Erez Perelman,Greg Hamerly,Brad Calder +3 more
- Vol. 30, Iss: 5, pp 45-57
TLDR
This work quantifies the effectiveness of Basic Block Vectors in capturing program behavior across several different architectural metrics, explores the large scale behavior of several programs, and develops a set of algorithms based on clustering capable of analyzing this behavior.Abstract:
Understanding program behavior is at the foundation of computer architecture and program optimization. Many programs have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ramifications for many architectural and compiler techniques, from thread scheduling, to feedback directed optimizations, to the way programs are simulated. However, in order to take advantage of time-varying behavior, we must first develop the analytical tools necessary to automatically and efficiently analyze program behavior over large sections of execution.Our goal is to develop automatic techniques that are capable of finding and exploiting the Large Scale Behavior of programs (behavior seen over billions of instructions). The first step towards this goal is the development of a hardware independent metric that can concisely summarize the behavior of an arbitrary section of execution in a program. To this end we examine the use of Basic Block Vectors. We quantify the effectiveness of Basic Block Vectors in capturing program behavior across several different architectural metrics, explore the large scale behavior of several programs, and develop a set of algorithms based on clustering capable of analyzing this behavior. We then demonstrate an application of this technology to automatically determine where to simulate for a program to help guide computer architecture research.read more
Citations
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Journal ArticleDOI
Pin: building customized program analysis tools with dynamic instrumentation
Chi-Keung Luk,Robert Cohn,Robert Muth,Harish Patil,Artur Klauser,Geoff Lowney,Steven Wallace,Vijay Janapa Reddi,Kim Hazelwood +8 more
TL;DR: The goals are to provide easy-to-use, portable, transparent, and efficient instrumentation, and to illustrate Pin's versatility, two Pintools in daily use to analyze production software are described.
Proceedings ArticleDOI
McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures
TL;DR: Combining power, area, and timing results of McPAT with performance simulation of PARSEC benchmarks at the 22nm technology node for both common in-order and out-of-order manycore designs shows that when die cost is not taken into account clustering 8 cores together gives the best energy-delay product, whereas when cost is taking into account configuring clusters with 4 cores gives thebest EDA2P and EDAP.
Proceedings ArticleDOI
Razor: a low-power pipeline based on circuit-level timing speculation
Daniel J. Ernst,Nam Sung Kim,Shidhartha Das,Sanjay Pant,Rajeev R. Rao,Toan Pham,Conrad H. Ziesler,David Blaauw,Todd Austin,Krisztian Flautner,Trevor Mudge +10 more
TL;DR: A solution by which the circuit can be operated even below the ‘critical’ voltage, so that no margins are required and thus more energy can be saved.
Benchmarking modern multiprocessors
Kai Li,Christian Bienia +1 more
TL;DR: A methodology to design effective benchmark suites is developed and its effectiveness is demonstrated by developing and deploying a benchmark suite for evaluating multiprocessors called PARSEC, which has been adopted by many architecture groups in both research and industry.
Proceedings ArticleDOI
A systematic methodology to compute the architectural vulnerability factors for a high-performance microprocessor
TL;DR: This paper identifies numerous cases, such as prefetches, dynamicallydead code, and wrong-path instructions, in which a fault will not affect correct execution, and shows AVFs of 28% and 9% for the instruction queue and execution units, respectively,averaged across dynamic sections of the entire CPU2000benchmark suite.
References
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Journal ArticleDOI
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