TY - GEN
T1 - Preliminary evaluation of a parallel trace replay tool for HPC network simulations
AU - Acun, Bilge
AU - Jain, Nikhil
AU - Bhatele, Abhinav
AU - Mubarak, Misbah
AU - Carothers, Christopher D.
AU - Kale, Laxmikant V.
N1 - Funding Information:
This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was funded by the LDRD Program at LLNL under project tracking code 13-ERD-055 (LLNL-CONF-667225).
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - This paper presents a preliminary evaluation of TraceR, a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging on interconnection networks. It addresses two major shortcomings in current network simulators. First, it enables fast and scalable simulations of large-scale supercomputer networks. Second, it can simulate production HPC applications using BigSim’s emulation framework. In addition to introducing TraceR, this paper studies the impact of input parameters on simulation performance. We also compare TraceR with other network simulators such as SST and BigSim, and demonstrate TraceR’s scalability using various case studies.
AB - This paper presents a preliminary evaluation of TraceR, a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging on interconnection networks. It addresses two major shortcomings in current network simulators. First, it enables fast and scalable simulations of large-scale supercomputer networks. Second, it can simulate production HPC applications using BigSim’s emulation framework. In addition to introducing TraceR, this paper studies the impact of input parameters on simulation performance. We also compare TraceR with other network simulators such as SST and BigSim, and demonstrate TraceR’s scalability using various case studies.
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U2 - 10.1007/978-3-319-27308-2_34
DO - 10.1007/978-3-319-27308-2_34
M3 - Conference contribution
AN - SCOPUS:84952000763
SN - 9783319273075
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 417
EP - 429
BT - Euro-Par 2015
A2 - Hunold, Sascha
A2 - Weidendorfer, Josef
A2 - Gimenez, Domingo
A2 - Ricci, Laura
A2 - Lankes, Stefan
A2 - Costan, Alexandru
A2 - Varbanescu, Ana Lucia
A2 - Scott, Stephen L.
A2 - Requena, María Engracia Gómez
A2 - Scarano, Vittorio
A2 - Iosup, Alexandru
A2 - Alexander, Michael
PB - Springer
T2 - International Workshops on Parallel Processing Workshops, Euro-Par 2015
Y2 - 24 August 2015 through 25 August 2015
ER -