Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis
Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis
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DOI：
10.1109/ispass57527.2023.00026
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发表时间：
2023-04
期刊：
影响因子：
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通讯作者：
Zhuren Liu;Shouzhe Zhang;Justin Garrigus;Hui Zhao
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文献类型：
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作者：
Zhuren Liu;Shouzhe Zhang;Justin Garrigus;Hui Zhao
基因组分析是对基因的研究，其中包括基因组特征的识别，测量或比较。基因组学研究对我们的社会至关重要，因为它可以用于检测疾病，创建疫苗并开发药物和治疗方法。作为具有大量并行处理能力的一种通用加速器，GPU最近已用于基因组学分析。开发用于基因组分析的基于GPUB的硬件和软件框架正在成为一个有希望的研究领域。为了支持这类研究，需要基准，以具有代表性，并发和多种应用程序的应用程序。在这项工作中，我们创建了一个名为Genomics-GPU的基准套件，其中包含10种广泛使用的基因组分析应用。它涵盖了DNA和RNA的基因组比较，匹配和聚类。我们还对这些应用程序进行了调整，以利用CUDA动态并行性（CDP）（CDP）（CDP），这是一个支持动态GPU编程的高级功能，以进一步提高性能。我们的基准套件可以作为算法优化的基础，也可以促进GPU架构开发进行基因组学分析。
Genomic analysis is the study of genes which includes the identification, measurement, or comparison of genomic features. Genomics research is of great importance to our society because it can be used to detect diseases, create vaccines, and develop drugs and treatments. As a type of general-purpose accelerators with massive parallel processing capability, GPUs have been recently used for genomics analysis. Developing GPUbased hardware and software frameworks for genome analysis is becoming a promising research area. To support this type of research, benchmarks are needed that can feature representative, concurrent, and diverse applications running on GPUs. In this work, we created a benchmark suite called Genomics-GPU, which contains 10 widely-used genomic analysis applications. It covers genome comparison, matching, and clustering for DNAs and RNAs. We also adapted these applications to exploit the CUDA Dynamic Parallelism (CDP), a recent advanced feature supporting dynamic GPU programming, to further improve the performance. Our benchmark suite can serve as a basis for algorithm optimization and also facilitate GPU architecture development for genomics analysis.