Rapid Indirect Trajectory Optimization on Highly Parallel Computing Architectures

Parallel Embedded Computing Architectures

Stochastic Gradient Descent on Highly-Parallel Architectures

There is an increased interest in building data analytics frameworks with advanced algebraic capabilities both in industry and academia. Many of these frameworks, e.g., TensorFlow and BIDMach, implement their computeintensive primitives in two flavors—as multi-thread routines for multi-core CPUs and as highly-parallel kernels executed on GPU. Stochastic gradient descent (SGD) is the most popula...

Scientiic Computing on Bulk Synchronous Parallel Architectures

Bulk synchronous parallel architectures o er the prospect of achieving both scalable parallel performance and architecture independent parallel software. They provide a robust model on which to base the future development of general purpose parallel computing systems. In this paper we theoretically and experimentally analyse the e ciency with which a wide range of important scienti c computatio...

Scientiic Computing on Bulk Synchronous Parallel Architectures

Bulk synchronous parallel BSP architectures o er the prospect of achieving both scalable parallel performance and architecture independent parallel software They pro vide a robust model on which to base the future development of general purpose parallel computing systems In this paper we theoretically and experimentally analyse the e ciency with which a wide range of important scienti c computa...

Scientific Computing on Bulk Synchronous Parallel Architectures

Bulk synchronous parallel architectures offer the prospect of achieving both scalable parallel performance and architecture independent parallel software. They provide a robust model on which to base the future development of general purpose parallel computing systems. In this paper we theoretically and experimentally analyse the efficiency with which a wide range of important scientific comput...