TY - GEN
T1 - Optically connected and reconfigurable GPU architecture for optimized peer-to-peer access
AU - Anderson, Erik
AU - González, Jorge
AU - Gazman, Alexander
AU - Azevedo, Rodolfo
AU - Bergman, Keren
N1 - Publisher Copyright:
© 2018 Copyright held by the owner/author(s).
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Increasing industry interest in the optimization of inter-GPU communication has motivated this work to explore new ways to enable peer-to-peer access. Specifically, this paper investigates how reconfigurable optical links between GPUs in multi-GPU servers can allow for minimized memory transfer latencies for given machine learning applications. Silicon photonics (SiP) is proposed as the enabling technology for such a reconfigurable architecture due to the potential for scalable and cost-efficient production. We evaluated our architecture using traffic obtained from an NVLink-connected 8 GPU server executing a set of machine learning models including AlexNet, DenseNet, NASNet, ResNet, MobileNet, and VGG16. Our results show up to 24.91% reduction of the total relative transmission latency (RTL) between peers.
AB - Increasing industry interest in the optimization of inter-GPU communication has motivated this work to explore new ways to enable peer-to-peer access. Specifically, this paper investigates how reconfigurable optical links between GPUs in multi-GPU servers can allow for minimized memory transfer latencies for given machine learning applications. Silicon photonics (SiP) is proposed as the enabling technology for such a reconfigurable architecture due to the potential for scalable and cost-efficient production. We evaluated our architecture using traffic obtained from an NVLink-connected 8 GPU server executing a set of machine learning models including AlexNet, DenseNet, NASNet, ResNet, MobileNet, and VGG16. Our results show up to 24.91% reduction of the total relative transmission latency (RTL) between peers.
UR - http://www.scopus.com/inward/record.url?scp=85060987011&partnerID=8YFLogxK
U2 - 10.1145/3240302.3240418
DO - 10.1145/3240302.3240418
M3 - Conference contribution
AN - SCOPUS:85060987011
T3 - ACM International Conference Proceeding Series
BT - MEMSYS 2018 - Proceedings of the International Symposium on Memory Systems
PB - Association for Computing Machinery
T2 - 2018 International Symposium on Memory Systems, MEMSYS 2018
Y2 - 1 October 2018 through 4 October 2018
ER -