Abstract—Stencil computations comprise the compute-intensive core of many scientific applications. The data access pattern of stencil computations often requires several adjacent data elements of arrays to be accessed in innermost parallel loops. Although such loops are vectorized by current compilers like GCC and ICC that target short-vector SIMD instruction sets, a number of redundant loads or additional intra-register data shuffle operations are required, reducing the achievable performance. Thus, even when all arrays are cache resident, the peak performance achieved with stencil computations is considerably lower than machine peak. In this paper, we present a hardware-based solution for this problem. We propose an extension to the stand...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Stencil computations arise in many scientific computing do-mains, and often represent time-critical ...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
Stencil computations are an integral component of applications in a number of scientific computing d...
Abstract. Stencil computations are at the core of applications in many domains such as computational...
Accelerating program performance via SIMD vector units is very common in modern processors, as evide...
Abstract—Current CPU and GPU architectures heavily use data and instruction parallelism at different...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
In the last years, there has been much effort in commercial compilers (icc, gcc) to exploit efficien...
So-called SIMD instructions, which trigger operations that process in each clock cycle a data tuple,...
Recent extensions to the Intel ® Architecture feature the SIMD technique to enhance the performance ...
An important class of problems used widely in both the embedded systems and scientific domains perfo...
Existing vectorization techniques are ineffective for loops that exhibit little loop-level paralleli...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Stencil computations arise in many scientific computing do-mains, and often represent time-critical ...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
Data-level parallelism is frequently ignored or underutilized. Achieved through vector/SIMD capabili...
Stencil computations are an integral component of applications in a number of scientific computing d...
Abstract. Stencil computations are at the core of applications in many domains such as computational...
Accelerating program performance via SIMD vector units is very common in modern processors, as evide...
Abstract—Current CPU and GPU architectures heavily use data and instruction parallelism at different...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
In the last years, there has been much effort in commercial compilers (icc, gcc) to exploit efficien...
So-called SIMD instructions, which trigger operations that process in each clock cycle a data tuple,...
Recent extensions to the Intel ® Architecture feature the SIMD technique to enhance the performance ...
An important class of problems used widely in both the embedded systems and scientific domains perfo...
Existing vectorization techniques are ineffective for loops that exhibit little loop-level paralleli...
International audienceIn many cases, applications are not optimized for the hardware on which they r...
Stencil computations arise in many scientific computing do-mains, and often represent time-critical ...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...