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Transcript of 1 PBB: A Parallel Bioinformatics Benchmark Suite for Shared Memory Multiprocessors CHEN Wenguang HPC...
![Page 1: 1 PBB: A Parallel Bioinformatics Benchmark Suite for Shared Memory Multiprocessors CHEN Wenguang HPC Inst., CS Dept., Tsinghua University.](https://reader035.fdocuments.net/reader035/viewer/2022062714/56649d1f5503460f949f2392/html5/thumbnails/1.jpg)
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PBB: A Parallel Bioinformatics
Benchmark Suite for Shared Memory Multiprocessors
CHEN WenguangHPC Inst., CS Dept., Tsinghua University
![Page 2: 1 PBB: A Parallel Bioinformatics Benchmark Suite for Shared Memory Multiprocessors CHEN Wenguang HPC Inst., CS Dept., Tsinghua University.](https://reader035.fdocuments.net/reader035/viewer/2022062714/56649d1f5503460f949f2392/html5/thumbnails/2.jpg)
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Outlines
• Motivation
• Benchmark selection & construction
• Benchmark characteristics
• Performance results
• Conclusions, Q&A
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Motivation
• Widely use of bioinformatics applications• The trend of multi-core
=> There should be a parallel bioinfo. benchmark
• SPEC CPU2000 may not match the characteristics of bioinformatics workloads well
• Existing bioinformatics benchmark are not satisfactory
=> We need a new one
![Page 4: 1 PBB: A Parallel Bioinformatics Benchmark Suite for Shared Memory Multiprocessors CHEN Wenguang HPC Inst., CS Dept., Tsinghua University.](https://reader035.fdocuments.net/reader035/viewer/2022062714/56649d1f5503460f949f2392/html5/thumbnails/4.jpg)
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Existing Bioinformatics Benchmarks:BioBench:
does not cover some important domains no parallel program
BioPerf: includes only one parallel benchmark
BioParallel:our previous work, includes 5 parallel application
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Being more complete
7 applications covering 7 of the most important domains of bioinfo.
Keeping pace with the changing world
all the applications are parallelized
PBB benchmark suite:
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Benchmark Selection & Construction
1. Identify the most important application domains
2. Choose representative applications for each domain
most popular, most advanced
3. Benchmark optimization & parallelization
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The 7 applications:
1. Pairwise sequence alignment: BLAST-P
2. Global alignment: PLSA
3. Multiple sequences alignment: MUSCLE
4. Protein 3D structure prediction: Rosetta
5. Phylogenetic tree reconstruction: SEMPHY
6. Gene regulatory network learning: ModuleNet
7. Pattern study of Single Nucleotide Polymorphisms: SNP
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Benchmark Characteristics
Systems Used:
Workload analysis is performed on QP001
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Instruction profile:
Higher L/S
Non-egligible FP
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CPI
Low CPI
8P means QP001 with HT enabled
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FSB bandwidth utilization
Low utilization
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Performance Results
Benchmark scores:
61 6
_ 100i
ii
rPBB Score
m
: time used to run application i on the reference system ir
im : time used to run application i on the tested system
Rosetta is excluded for it produces random results
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Scores of PBB
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Parallel speedup
Tested on Unisys-ES700 with 16 Xeon
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Hyper Threading Effects
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Conclusions
Workload characteristics:
1. High percentage of load/store instructions
2. Non-negligible floating point instructions, but still significantly lower than SPECCPU 2000FP
3. Low CPI
4. Low memory bandwidth demand
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Thanks
Any questions?