4 papers
Automatic MILP Solver Configuration By Learning Problem Similarities
Abdelrahman Hosny, Sherief Reda
A large number of real-world optimization problems can be formulated as Mixed Integer Linear Programs (MILP). MILP solvers expose numerous configuration parameters to control their…
BitTrain: Sparse Bitmap Compression for Memory-Efficient Training on the Edge
Abdelrahman Hosny, Marina Neseem, Sherief Reda
Training on the Edge enables neural networks to learn continuously from new data after deployment on memory-constrained edge devices. Previous work is mostly concerned with reducin…
Characterizing and Optimizing EDA Flows for the Cloud
Abdelrahman Hosny, Sherief Reda
Cloud computing accelerates design space exploration in logic synthesis, and parameter tuning in physical design. However, deploying EDA jobs on the cloud requires EDA teams to dee…
DRiLLS: Deep Reinforcement Learning for Logic Synthesis
Abdelrahman Hosny, Soheil Hashemi, Mohamed Shalan +1
Logic synthesis requires extensive tuning of the synthesis optimization flow where the quality of results (QoR) depends on the sequence of optimizations used. Efficient design spac…