TY - GEN
T1 - Investigating Nvidia GPU Architecture Trends via Microbenchmarks
AU - Zhang, Lingqi
AU - Barton, Ryan
AU - Chen, Peng
AU - Wang, Xiao
AU - Endo, Toshio
AU - Matsuoka, Satoshi
AU - Wahib, Mohamed
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In recent years, GPUs have become crucial tools in high performance computing. To understand the evolution of these devices, we conducted a study analyzing hardware trends in GPUs. This information provides valuable insights into GPU programming and emerging trends in this field. We mainly focus on three features: the floating-point operations per second (FLOPS) of floating-point units (FPUs), device memory access, and machine balance.
AB - In recent years, GPUs have become crucial tools in high performance computing. To understand the evolution of these devices, we conducted a study analyzing hardware trends in GPUs. This information provides valuable insights into GPU programming and emerging trends in this field. We mainly focus on three features: the floating-point operations per second (FLOPS) of floating-point units (FPUs), device memory access, and machine balance.
KW - GPUs
KW - Microbenchmarks
UR - https://www.scopus.com/pages/publications/85211786424
U2 - 10.1109/CLUSTERWorkshops61563.2024.00045
DO - 10.1109/CLUSTERWorkshops61563.2024.00045
M3 - Conference contribution
AN - SCOPUS:85211786424
T3 - Proceedings - 2024 IEEE International Conference on Cluster Computing Workshops, CLUSTER Workshops 2024
SP - 174
EP - 175
BT - Proceedings - 2024 IEEE International Conference on Cluster Computing Workshops, CLUSTER Workshops 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Cluster Computing Workshops, CLUSTER Workshops 2024
Y2 - 24 September 2024 through 27 September 2024
ER -