26 citations · 43 across the 11 of their papers we have counts for
4 papers · 1 filter
Cloud Collectives: Towards Cloud-aware Collectives forML Workloads with Rank Reordering
Liang Luo, Jacob Nelson, Arvind Krishnamurthy +1
ML workloads are becoming increasingly popular in the cloud. Good cloud training performance is contingent on efficient parameter exchange among VMs. We find that Collectives, the…
Enumerating Hardware-Software Splits with Program Rewriting
Gus Smith, Zachary Tatlock, Luis Ceze
A core problem in hardware-software codesign is in the sheer size of the design space. Without a set ISA to constrain the hardware-software interface, the design space explodes. Th…
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training
Liang Luo, Jacob Nelson, Luis Ceze +2
Distributed deep neural network (DDNN) training constitutes an increasingly important workload that frequently runs in the cloud. Larger DNN models and faster compute engines are s…
The Impact of Memory Models on Software Reliability in Multiprocessors
Alexander Jaffe, Thomas Moscibroda, Laura Effinger-Dean +2
The memory consistency model is a fundamental system property characterizing a multiprocessor. The relative merits of strict versus relaxed memory models have been widely debated i…