105 citations · 105 across the 1 of their papers we have counts for
2 papers
cs.DC2018
ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler
Matthew Sotoudeh, Anand Venkat, Michael Anderson +3
Domain specific accelerators present new challenges and opportunities for code generation onto novel instruction sets, communication fabrics, and memory architectures. In this pape…
cs.DC2018★ 105 cited
Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning
Scott Cyphers, Arjun K. Bansal, Anahita Bhiwandiwalla +18
The Deep Learning (DL) community sees many novel topologies published each year. Achieving high performance on each new topology remains challenging, as each requires some level of…