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data analysis
Reproducible Performance Benchmarking for Genomics Workflows on HPC Cluster
Hi! I’m Martin, and I will be working on Reproducible Performance Benchmarking for Genomics Workflows on HPC Cluster under the mentorship of In Kee Kim. Our work is driven by the scale of computing systems that hosts data commons – we believe that performance characterization of genomics workload should be done rapidly and at the scale similar to production settings.
Martin L. Putra
Jun 12, 2024
Reproducible Performance Benchmarking for Genomics Workflows on HPC Cluster
Project Idea description We aim to characterize the performance of genomic workflows on HPC clusters by conducting two research activities using a broad set of state-of-the-art genomic applications and open-source datasets.
In Kee Kim
Reproducible Analysis & Models for Predicting Genomics Workflow Execution Time
A high-throughput workflow execution system is needed to continuously gain insights from th e increasingly abundant genomics data. However, genomics workflows often have long execution times (e.g., hours to days) due to their large input files.
In Kee Kim
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