Archive of posts tagged: Accelerators
Building Performance Scalable and Composable Machine Learning Accelerators
To meet machine learning (ML) practitioners’ insatiable demand for higher processing power, computer architects have been at the forefront of developing accelerated computing solutions for ML that fundamentally changed the landscape of the computing industry. Given...
Rethinking Neural Network Dataflow in Larger Scales
Deep learning, with its most representative algorithm, deep neural networks, has been the primary driving force for the recent rapid development of high-performance computing systems. Hardware researchers are proposing a large number of specialized chip architectures...
Posit: A Potential Replacement for IEEE 754
Motivation Number systems and computer arithmetics are essential for designing efficient hardware and software architecture. In particular, real-valued computation constitutes a crucial component in almost all forms of today’s computing systems from mobile devices to...
NSF Workshop Report on Future Directions for Parallel and Distributed Computing
Due to technology challenges and potential societal benefits, NSF has provided sustained funding for issues surrounding effective scaling of parallel and distributed computing, including through the Exploiting Parallelism and Scalability(XPS) Program, begun in 2012,...Subscribe
