Titlebook: Euro-Par 2015: Parallel Processing Workshops; Euro-Par 2015 Intern Sascha Hunold,Alexandru Costan,Michael Alexander Conference proceedings

婚姻生活

https://doi.org/10.1007/978-3-662-40435-5(FEM) leads to huge systems of equations whose solutions often require parallel computing. The practical course presented in this paper aims at introducing the FEM as well as the concept of parallel computing to students with the help of a FEM library, in this case HiFlow.. To achieve this goal, the

背景

https://doi.org/10.1007/978-3-642-65526-5terfly transformations for which we developed efficient implementations on heterogeneous architectures. We used both Graphics Processing Units and Intel Xeon Phi as accelerators. The performance results show that the pre-processing due to randomization is negligible and that the solver outperforms t

代替

集中營

Slit-Lamp

dilute

我怕被刺穿

Tools - Visualizing Thread Access on Java Objects using Lightweight Runtime Monitoringy one class for the monitoring at the same time and by a fast logging implementation. A producer/consumer program and a program for cooperative task execution are used to demonstrate the applicability and the performance of the logging. . tools can be used to understand and optimize thread synchronization in Java programs.

Ambulatory

Identifying Optimization Opportunities Within Kernel Execution in GPU Codesof our techniques with LAMMPS and LULESH application case studies on a variety of GPU architectures. By sampling instruction mixes for kernel execution runs, we reveal a variety of intrinsic program characteristics relating to computation, memory and control flow.

alliance

Parallel Computing vs. Distributed Computing: A Great Confusion? (Position Paper)n everything (and reciprocally)” attitude does not seem to be a relevant approach to teach students the important concepts which characterize parallelism on the one side, and distributed computing on the other side.

無聊點(diǎn)好

A Randomized LU-based Solver Using GPU and Intel Xeon Phi Acceleratorsel Xeon Phi as accelerators. The performance results show that the pre-processing due to randomization is negligible and that the solver outperforms the corresponding routines based on partial pivoting.