1 citations · 1 across the 2 of their papers we have counts for
4 papers
Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP
Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid +5
Resource allocation problems in many computer systems can be formulated as mathematical optimization problems. However, finding exact solutions to these problems using off-the-shel…
Don't Give Up on Large Optimization Problems; POP Them!
Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid +2
Resource allocation problems in many computer systems can be formulated as mathematical optimization problems. However, finding exact solutions to these problems using off-the-shel…
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference
Peter Kraft, Daniel Kang, Deepak Narayanan +3
Systems for ML inference are widely deployed today, but they typically optimize ML inference workloads using techniques designed for conventional data serving workloads and miss cr…
Automatic Parallelization of Sequential Programs
Peter Kraft, Amos Waterland, Daniel Y Fu +3
Prior work on Automatically Scalable Computation (ASC) suggests that it is possible to parallelize sequential computation by building a model of whole-program execution, using that…