SCHEDULE: NOV 10-16, 2012
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Auto-Tuning of Parallel IO Parameters for HDF5 Applications
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Babak Behzad, Joey Huchette, Huong Luu, Ruth Aydt, Quincey Koziol, Mr Prabhat, Suren Byna, Mohamad Chaarawi, Yushu Yao
ROOM:East Entrance
ABSTRACT:
I/O is often a limiting factor for HPC applications. Although well-tuned codes have shown good I/O throughput compared to the theoretical maximum, the majority of applications use default parallel I/O parameter values and achieve poor performance.
We have built an extensible framework for benchmark-guided auto-tuning of HDF5, MPI-IO, and Lustre parameters. The framework includes three main components. H5AutoTuner uses a control file to adjust I/O parameters without changing or recompiling the application. H5PerfCapture records performance metrics for HDF5 and MPI-IO. H5Evolve uses genetic algorithms to explore the parameter search space until well-performing values are identified. Early results for three HDF5 application-based I/O benchmarks on two different HPC systems have shown
1.3x6.8x speedup using auto-tuned parameters compared to default values.
Our auto-tuning framework can improve I/O performance without hands-on optimization and also provides a general platform for exploring parallel I/O behavior.
The printed poster details framework architecture and experimental results.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Babak Behzad - University of Illinois at Urbana-Champaign
Joey Huchette - Lawrence Berkeley National Laboratory
Huong Luu - University of Illinois at Urbana-Champaign
Ruth Aydt - HDF Group
Quincey Koziol - HDF Group
Mr Prabhat - Lawrence Berkeley National Laboratory
Suren Byna - Lawrence Berkeley National Laboratory
Mohamad Chaarawi - HDF Group
Yushu Yao - Lawrence Berkeley National Laboratory
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Auto-Tuning of Parallel IO Parameters for HDF5 Applications
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Babak Behzad, Joey Huchette, Huong Luu, Ruth Aydt, Quincey Koziol, Mr Prabhat, Suren Byna, Mohamad Chaarawi, Yushu Yao
ROOM:East Entrance
ABSTRACT:
I/O is often a limiting factor for HPC applications. Although well-tuned codes have shown good I/O throughput compared to the theoretical maximum, the majority of applications use default parallel I/O parameter values and achieve poor performance.
We have built an extensible framework for benchmark-guided auto-tuning of HDF5, MPI-IO, and Lustre parameters. The framework includes three main components. H5AutoTuner uses a control file to adjust I/O parameters without changing or recompiling the application. H5PerfCapture records performance metrics for HDF5 and MPI-IO. H5Evolve uses genetic algorithms to explore the parameter search space until well-performing values are identified. Early results for three HDF5 application-based I/O benchmarks on two different HPC systems have shown
1.3x6.8x speedup using auto-tuned parameters compared to default values.
Our auto-tuning framework can improve I/O performance without hands-on optimization and also provides a general platform for exploring parallel I/O behavior.
The printed poster details framework architecture and experimental results.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Babak Behzad - University of Illinois at Urbana-Champaign
Joey Huchette - Lawrence Berkeley National Laboratory
Huong Luu - University of Illinois at Urbana-Champaign
Ruth Aydt - HDF Group
Quincey Koziol - HDF Group
Mr Prabhat - Lawrence Berkeley National Laboratory
Suren Byna - Lawrence Berkeley National Laboratory
Mohamad Chaarawi - HDF Group
Yushu Yao - Lawrence Berkeley National Laboratory
Click here to download .ics calendar file