Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
- Even though state-of-the-art FPGAs present new opportunities in exploring low-cost high-performance architectures for floating-point scientific applications, they also pose serio...
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Compared to Krylov space methods based on orthogonal or oblique projection, the Chebyshev iteration does not require inner products and is therefore particularly suited for massiv...
When using a shared memory multiprocessor, the programmer faces the selection of the portable programming model which will deliver the best performance. Even if he restricts his c...