Breaking the mold: overcoming the time constraints of molecular dynamics on general-purpose hardware
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arXiv
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| Autori principali: | , , , , , , , , , , , , , |
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| Natura: | Preprint |
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2024
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| _version_ | 1866915159936598016 |
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| author | Perez, Danny Thompson, Aidan Moore, Stan Oppelstrup, Tomas Sharapov, Ilya Santos, Kylee Sharifian, Amirali Kalchev, Delyan Z. Schreiber, Robert Pakin, Scott Leon, Edgar A. Laros III, James H. James, Michael Rajamanickam, Sivasankaran |
| author_facet | Perez, Danny Thompson, Aidan Moore, Stan Oppelstrup, Tomas Sharapov, Ilya Santos, Kylee Sharifian, Amirali Kalchev, Delyan Z. Schreiber, Robert Pakin, Scott Leon, Edgar A. Laros III, James H. James, Michael Rajamanickam, Sivasankaran |
| contents | The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have however failed to provide strong scaling for MD as scale-out CPU and GPU platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras Wafer Scale Engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144M steps/second for 200,000 atoms whose interactions are described by an Embedded Atom Method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10532 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Breaking the mold: overcoming the time constraints of molecular dynamics on general-purpose hardware Perez, Danny Thompson, Aidan Moore, Stan Oppelstrup, Tomas Sharapov, Ilya Santos, Kylee Sharifian, Amirali Kalchev, Delyan Z. Schreiber, Robert Pakin, Scott Leon, Edgar A. Laros III, James H. James, Michael Rajamanickam, Sivasankaran Distributed, Parallel, and Cluster Computing Materials Science Computational Physics The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have however failed to provide strong scaling for MD as scale-out CPU and GPU platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras Wafer Scale Engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144M steps/second for 200,000 atoms whose interactions are described by an Embedded Atom Method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. |
| title | Breaking the mold: overcoming the time constraints of molecular dynamics on general-purpose hardware |
| topic | Distributed, Parallel, and Cluster Computing Materials Science Computational Physics |
| url | https://arxiv.org/abs/2411.10532 |