2 citations · 3 across the 3 of their papers we have counts for
5 papers
MAFIA: Machine Learning Acceleration on FPGAs for IoT Applications
Nikhil Pratap Ghanathe, Vivek Seshadri, Rahul Sharma +2
Recent breakthroughs in ML have produced new classes of models that allow ML inference to run directly on milliwatt-powered IoT devices. On one hand, existing ML-to-FPGA compilers…
On Scaling Data-Driven Loop Invariant Inference
Sahil Bhatia, Saswat Padhi, Nagarajan Natarajan +2
Automated synthesis of inductive invariants is an important problem in software verification. Once all the invariants have been specified, software verification reduces to checking…
Overfitting in Synthesis: Theory and Practice (Extended Version)
Saswat Padhi, Todd Millstein, Aditya Nori +1
In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatically generate a program belonging to a grammar of possible implementations that meets a logical specificatio…
Eventually Sound Points-To Analysis with Missing Code
Osbert Bastani, Lazaro Clapp, Saswat Anand +2
Static analyses make the increasingly tenuous assumption that all source code is available for analysis; for example, large libraries often call into native code that cannot be ana…
Stochastic Superoptimization
Eric Schkufza, Rahul Sharma, Alex Aiken
We formulate the loop-free, binary superoptimization task as a stochastic search problem. The competing constraints of transformation correctness and performance improvement are en…