8 citations · 13 across the 2 of their papers we have counts for
4 papers
Learned Hardware/Software Co-Design of Neural Accelerators
Zhan Shi, Chirag Sakhuja, Milad Hashemi +2
The use of deep learning has grown at an exponential rate, giving rise to numerous specialized hardware and software systems for deep learning. Because the design space of deep lea…
An Imitation Learning Approach for Cache Replacement
Evan Zheran Liu, Milad Hashemi, Kevin Swersky +2
Program execution speed critically depends on increasing cache hits, as cache hits are orders of magnitude faster than misses. To increase cache hits, we focus on the problem of ca…
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Will Grathwohl, Kuan-Chieh Wang, Jörn-Henrik Jacobsen +3
We propose to reinterpret a standard discriminative classifier of p(y|x) as an energy based model for the joint distribution p(x,y). In this setting, the standard class probabiliti…
Learning Execution through Neural Code Fusion
Zhan Shi, Kevin Swersky, Daniel Tarlow +2
As the performance of computer systems stagnates due to the end of Moore's Law, there is a need for new models that can understand and optimize the execution of general purpose cod…