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pro vyhledávání: '"Fox, Alyson"'
Autor:
Fox, Alyson, Lindstrom, Peter
The amount of data generated and gathered in scientific simulations and data collection applications is continuously growing, putting mounting pressure on storage and bandwidth concerns. A means of reducing such issues is data compression; however, l
Externí odkaz:
http://arxiv.org/abs/2407.01826
Publikováno v:
SIAM Journal on Scientific Comptuing, Volume 46, Issue 5 (2024)
Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing env
Externí odkaz:
http://arxiv.org/abs/2206.08479
Autor:
Testa, G., Gupta, A., Lee, S., Fricker, Z., Hashimoto, K., Kwon, D., Emond, J., Fox, A., Samstein, B., Brown, R., Rosenblatt, R., Kubal, A., Gilroy, R., King, E., Heimbach, J., Taner, T., Watt, K., Chacko, K., von Ahrens, D., Fortune, B., Florman, S., Schiano, T., Liapakis, A., Griesemer, A., Orandi, B., Caicedo, J., Dietch, Z., Ganger, D., Duarte, A., Ravindra, K., Kappus, M., Melcher, M., Bhan, I., Tholey, D., Kaplan, A., Anderson, B., Selzner, N., Roberts, J.P., Pillai, A., DiSabato, D., Pomfret, E., Jackson, W., Maluf, D., Sonnenday, C., Bloom, P., Haakinson, D., Chinnakotla, S., Aby, E., Olthoff, K., Abu-Gazala, S., Bittermann, T., Abt, P., Humar, A., Ganesh, S., Bambha, K., Biggins, S., Hernandez-Alejandro, R., Tomiyama, K., Emamaullee, J., Kaur, N., Han, H., Klair, T., Yamaguchi, S., Cullen, J., Baker, T., Kim, R., Goldaracena, N., Sturdevant, M., Kwon, Y., Garonzik-Wang, J., Al-Adra, D., Shingina, A., Rizzari, M., Mulligan, D., Rubman, S., Batra, R., Batisti, J., Kaplan, Alyson, Aby, Elizabeth S., Scott, Sonia, Sonnenday, Christopher, Fox, Alyson, Mathur, Amit, Olthoff, Kim, Heimbach, Julie, Ladin, Keren, Emamaullee, Juliet
Publikováno v:
In American Journal of Transplantation October 2024 24(10):1742-1754
Autor:
Dunton, Alec Michael, Fox, Alyson
Renewed interest in mixed-precision algorithms has emerged due to growing data capacity and bandwidth concerns, as well as the advancement of GPUs, which enable significant speedup for low precision arithmetic. In light of this, we propose a mixed-pr
Externí odkaz:
http://arxiv.org/abs/2012.00706
Currently, the dominating constraint in many high performance computing applications is data capacity and bandwidth, in both inter-node communications and even more-so in on-node data motion. A new approach to address this limitation is to make use o
Externí odkaz:
http://arxiv.org/abs/2003.02324
Akademický článek
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Akademický článek
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Although mixed precision arithmetic has recently garnered interest for training dense neural networks, many other applications could benefit from the speed-ups and lower storage cost if applied appropriately. The growing interest in employing mixed p
Externí odkaz:
http://arxiv.org/abs/1912.06217
Compression of floating-point data will play an important role in high-performance computing as data bandwidth and storage become dominant costs. Lossy compression of floating-point data is powerful, but theoretical results are needed to bound its er
Externí odkaz:
http://arxiv.org/abs/1805.00546
Publikováno v:
SIAM Journal on Scientific Computing; 2024, Vol. 46 Issue 5, pA3258-A3281, 24p