14 citations · 29 across the 5 of their papers we have counts for
5 papers
SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling
Zikun Liu, Liang Luo, Qianru Li +31
Recent advances in recommendation scaling laws have led to foundation models of unprecedented complexity. While these models offer superior performance, their computational demands…
Execution Templates: Caching Control Plane Decisions for Strong Scaling of Data Analytics
Omid Mashayekhi, Hang Qu, Chinmayee Shah +1
Control planes of cloud frameworks trade off between scheduling granularity and performance. Centralized systems schedule at task granularity, but only schedule a few thousand task…
Scalable, Fast Cloud Computing with Execution Templates
Omid Mashayekhi, Hang Qu, Chinmayee Shah +1
Large scale cloud data analytics applications are often CPU bound. Most of these cycles are wasted: benchmarks written in C++ run 10-51 times faster than frameworks such as Naiad a…
Distributed Graphical Simulation in the Cloud
Omid Mashayekhi, Chinmayee Shah, Hang Qu +2
Graphical simulations are a cornerstone of modern media and films. But existing software packages are designed to run on HPC nodes, and perform poorly in the computing cloud. These…
Canary: A Scheduling Architecture for High Performance Cloud Computing
Hang Qu, Omid Mashayekhi, David Terei +1
We present Canary, a scheduling architecture that allows high performance analytics workloads to scale out to run on thousands of cores. Canary is motivated by the observation that…