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The element-by-element computation used in matrix-vector multiplications is the key kernel for attaining high-performance in unstructured implicit low-order finite-element earthquake simulations. We accelerate this CPU-based element-by-element kernel by ...

In this paper we explore the performance portability of directives provided by OpenMP 4 and OpenACC to program various types of node architectures with attached accelerators, both self-hosted multicore and offload multicore/GPU. Our goal is to examine ...

Modern computers with multi-/many-core processors and accelerators feature a sophisticated and deep memory hierarchy, potentially including distinct main memory, high-bandwidth memory, texture memory and scratchpad memory. The performance ...

In this paper, aiming at realizing directive-based temporal blocking for out-of-core stencil computation, we present an extension of OpenACC directives and a source-to-source translator capable of accelerating out-of-core stencil computation on a ...

OpenACC's programming model presents a simple interface to programmers, offering a trade-off between performance and development effort. OpenACC relies on compiler technologies to generate efficient code and optimize for performance. Among the difficult ...

Exposing opportunities for parallelization while explicitly managing data locality is the primary challenge to porting and optimizing existing computational science simulation codes to improve performance and accuracy. OpenMP provides many mechanisms ...

While GPUs are increasingly popular for high-performance computing, optimizing the performance of GPU programs is a time-consuming and non-trivial process in general. This complexity stems from the low abstraction level of standard GPU programming ...

As the HPC and Big Data communities continue to converge, heterogeneous and distributed systems are becoming commonplace. In order to take advantage of the immense computing power of these systems, distributing data efficiently and leveraging ...