We present a comparison of several modern C++ libraries providing high-level interfaces for programming multi- and many-core architectures on top of CUDA or OpenCL
To enhance the energy efficiency and performance of algorithms with Graphics Processing Unit (GPU) accelerators in source-code development, we consider the power efficiency based on data transfer bandwidth and power consumption in key situations
NCSA will host two courses offered by the Virtual School of Computational Science and Engineering (VSCSE) this summer: Programming Heterogeneous Parallel Computing Systems and…
Most of the time is spent discussing VC11′s Auto-Vectorizer with a few short forays into other VC compiler improvements (like Auto-Parallelizer).
How do we write good code? What principles, techniques, and idioms can we exploit to make it easier to produce quality code? In this presentation, I make an argument for type-rich interfaces, compact data structures, integrated resource management and error handling, and highly-structured algorithmic code.
Microsoft on Friday announced the publication of the C++ Accelerated Massive Parallelism (AMP) specification. This specification lets C++ developers write programs that can compile and execute on data-parallel hardware like discrete graphics cards or the SIMD vector instruction set in a processor.
The High Performance Computing Center Stuttgart (HLRS) opened the registration for the following course: “Fortran for Scientific Computing”
We show various usage scenarios of our PDL and demonstrate the effectiveness of our framework for a commonly used scientific kernel and a financial application on different configurations of a state-of-the-art CPU/GPU system.
The PAPP workshop focuses on practical aspects of high-level parallel programming: design, implementation and optimisation of high-level programming languages, semantics of parallel languages, formal verification, design or certification of libraries, middle-wares and tools