Statistical simulation: adding efficiency to the computer designer's toolbox
TL;DR: Statistical simulation enables quick and accurate design decisions in the early stages of computer design, at the processor and system levels, reducing total design time and cost.
read more
Abstract: Statistical simulation enables quick and accurate design decisions in the early stages of computer design, at the processor and system levels. it complements detailed but slower architectural simulations, reducing total design time and cost.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Benchmarking modern multiprocessors
Kai Li,Christian Bienia +1 more
- 01 Jan 2011
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.
1.1K
Efficiently exploring architectural design spaces via predictive modeling
Engin Ipek,Sally A. McKee,Rich Caruana,Bronis R. de Supinski,Martin Schulz +4 more
- 20 Oct 2006
TL;DR: This work builds accurate, confident predictive design-space models that produce highly accurate performance estimates for other points in the space, can be queried to predict performance impacts of architectural changes, and are very fast compared to simulation, enabling efficient discovery of tradeoffs among parameters in different regions.
An Evaluation of High-Level Mechanistic Core Models
TL;DR: This article explores, analyze, and compares the accuracy and simulation speed of high-abstraction core models, a potential solution to slow cycle-level simulation, and introduces the instruction-window centric (IW-centric) core model, a new mechanistic core model that bridges the gap between interval simulation and cycle-accurate simulation by enabling high-speed simulations with higher levels of detail.
•Book
Workload Modeling for Computer Systems Performance Evaluation
Dror G. Feitelson
- 01 Mar 2015
TL;DR: Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system.
305
A mechanistic performance model for superscalar out-of-order processors
TL;DR: The mechanistic model provides several advantages over prior modeling approaches, and, when estimating performance, it differs from detailed simulation of a 4-wide out-of-order processor by an average of 7%.
205
References
SimpleScalar: an infrastructure for computer system modeling
TL;DR: The SimpleScalar tool set provides an infrastructure for simulation and architectural modeling that can model a variety of platforms ranging from simple unpipelined processors to detailed dynamically scheduled microarchitectures with multiple-level memory hierarchies.
1.8K
Automatically characterizing large scale program behavior
Timothy Sherwood,Erez Perelman,Greg Hamerly,Brad Calder +3 more
- 01 Oct 2002
TL;DR: 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.
Asim: a performance model framework
Joel Emer,Pritpal S. Ahuja,E. Borch,Artur Klauser,Chi-Keung Luk,S. Manne,Shubhendu S. Mukherjee,Harish Patil,Steven Wallace,Nathan Binkert,Roger Espasa,Toni Juan +11 more
TL;DR: Asim provides a modular and reusable framework for creating many models that helps break down the performance-modeling problem into individual pieces that can be modeled separately, while its reusability allows using a software component repeatedly in different contexts.
256
Reducing state loss for effective trace sampling of superscalar processors
Thomas M. Conte,Mary Ann Hirsch,Kishore N. Menezes +2 more
- 07 Oct 1996
TL;DR: A fast and accurate method for statistical trace sampling of superscalar processors is proposed, which will help improve the quality of processor performance analysis in the development stage of system design.
191