TY - JOUR
T1 - XaaS
T2 - Acceleration as a Service to Enable Productive High-Performance Cloud Computing
AU - Hoefler, Torsten
AU - Copik, Marcin
AU - Beckman, Pete
AU - Jones, Andrew
AU - Foster, Ian
AU - Parashar, Manish
AU - Reed, Daniel
AU - Troyer, Matthias
AU - Schulthess, Thomas
AU - Ernst, Daniel
AU - Dongarra, Jack
N1 - Publisher Copyright:
© 1999-2011 IEEE.
PY - 2024
Y1 - 2024
N2 - High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function as a Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless computing while supporting long-running and performance-sensitive workloads from HPC.
AB - High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function as a Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless computing while supporting long-running and performance-sensitive workloads from HPC.
UR - https://www.scopus.com/pages/publications/85190170264
U2 - 10.1109/MCSE.2024.3382154
DO - 10.1109/MCSE.2024.3382154
M3 - Article
AN - SCOPUS:85190170264
SN - 1521-9615
VL - 26
SP - 40
EP - 51
JO - Computing in Science and Engineering
JF - Computing in Science and Engineering
IS - 3
ER -