New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code
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- Michel Müller
- Tokyo Institute of Technology, Meguro-ku, Tokyo
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- Takayuki Aoki
- Tokyo Institute of Technology, Meguro-ku, Tokyo
抄録
<jats:p>We introduce “Hybrid Fortran,” a new approach that allows a high-performance GPGPU port for structured grid Fortran codes. This technique only requires minimal changes for a CPU targeted codebase, which is a significant advancement in terms of productivity. It has been successfully applied to both dynamical core and physical processes of ASUCA, a Japanese mesoscale weather prediction model with more than 150k lines of code. By means of a minimal weather application that resembles ASUCA’s code structure, Hybrid Fortran is compared to both a performance model as well as today’s commonly used method, OpenACC. As a result, the Hybrid Fortran implementation is shown to deliver the same or better performance than OpenACC, and its performance agrees with the model both on CPU and GPU. In a full-scale production run, using an ASUCA grid with 1581 × 1301 × 58 cells and real-world weather data in 2km resolution, 24 NVIDIA Tesla P100 running the Hybrid Fortran–based GPU port are shown to replace more than fifty 18-core Intel Xeon Broadwell E5-2695 v4 running the reference implementation—an achievement comparable to more invasive GPGPU rewrites of other weather models.</jats:p>
収録刊行物
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- ACM Transactions on Parallel Computing
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ACM Transactions on Parallel Computing 5 (2), 1-42, 2018-06-30
Association for Computing Machinery (ACM)
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キーワード
詳細情報 詳細情報について
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- CRID
- 1363107368435403776
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- DOI
- 10.1145/3291523
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- ISSN
- 23294957
- 23294949
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- データソース種別
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- Crossref