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Title: Tools for Simulation and Benchmark Generation at Exascale

Abstract

The path to exascale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events and memory profiles, but can be extended to other areas, such as I/O, control flow, and data flow. It further focuses on extreme-scale simulation of millions of Message Passing Interface (MPI) ranks using a lightweight parallel discrete event simulation (PDES) toolkit for performance evaluation. Instead of simply replaying a trace within a simulation, the approach is to generate a benchmark from it and to run this benchmark within a simulation using models to reflect the performance characteristics of future-generation HPC systems. This provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work utilizes the ScalaTrace tool to generate scalable tracemore » files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to run the benchmark within a simulation.« less

Authors:
 [1];  [1];  [2]
  1. North Carolina State University
  2. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1185447
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 7th Parallel Tools Workshop, Dresden, Germany, 20130903, 20130904
Country of Publication:
United States
Language:
English

Citation Formats

Lagadapati, Mahesh, Mueller, Frank, and Engelmann, Christian. Tools for Simulation and Benchmark Generation at Exascale. United States: N. p., 2013. Web.
Lagadapati, Mahesh, Mueller, Frank, & Engelmann, Christian. Tools for Simulation and Benchmark Generation at Exascale. United States.
Lagadapati, Mahesh, Mueller, Frank, and Engelmann, Christian. Tue . "Tools for Simulation and Benchmark Generation at Exascale". United States.
@article{osti_1185447,
title = {Tools for Simulation and Benchmark Generation at Exascale},
author = {Lagadapati, Mahesh and Mueller, Frank and Engelmann, Christian},
abstractNote = {The path to exascale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events and memory profiles, but can be extended to other areas, such as I/O, control flow, and data flow. It further focuses on extreme-scale simulation of millions of Message Passing Interface (MPI) ranks using a lightweight parallel discrete event simulation (PDES) toolkit for performance evaluation. Instead of simply replaying a trace within a simulation, the approach is to generate a benchmark from it and to run this benchmark within a simulation using models to reflect the performance characteristics of future-generation HPC systems. This provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work utilizes the ScalaTrace tool to generate scalable trace files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to run the benchmark within a simulation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2013},
month = {1}
}

Conference:
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