Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Parallel programming continues to be difficult, despite substantial and ongoing research aimed at making it tractable. Especially dismaying is the gulf between theory and the pract...
Memetic algorithms have become to gain increasingly important for solving large scale combinatorial optimization problems. Typically, the extent of the application of local search...
This paper addresses the problem of extracting coarse-grained parallelism from large sequential code. It builds on BOP, a system for software speculative parallelization. BOP lets...
Writing correct distributed programs is hard. In spite of extensive testing and debugging, software faults persist even in commercial grade software. Many distributed systems, esp...