Analytical performance estimation during code generation on modern GPUs

Towards Automatic Code Generation for GPUs⋆

Abstract. Graphics Processing Units (GPUs) have become highly parallel and programmable systems used as commodity data-parallel coprocessors. Moreover manufacturers have developed new software interfaces that facilitate their use. Thus, new compilation strategies that enable automatic mapping of sequential code would very likely arise in the near future. To open this path, we need to define som...

Image Processing on Modern CPUs and GPUs

GPU-UniCache: Automatic Code Generation of Spatial Blocking for Stencils on GPUs

Spatial blocking is a critical memory-access optimization to efficiently exploit the computing resources of parallel processors, such as many-core GPUs. By reusing cache-loaded data over multiple spatial iterations, spatial blocking can significantly lessen the pressure of accessing slow global memory. Stencil computations, for example, can exploit such data reuse via spatial blocking through t...

Evaluation of state-of-the-art polyhedral tools for automatic code generation on GPUs

At present, multi-core and manycore platforms lead the computer industry, forcing software developers to adopt new programming paradigms, in order to fully exploit their computing capabilities. Nowadays, Graphics Processing Units (GPUs) are one of representatives of many-core architectures, and certainly the most widespread. This paper evaluates and compares tool frameworks that automatically g...

High-Quality Point-Based Rendering on Modern GPUs

In the last years point-based rendering has been shown to offer the potential to outperform traditional triangle based rendering both in speed and visual quality when it comes to processing highly complex models. Existing surface splatting techniques achieve superior visual quality by proper filtering but they are still limited in rendering speed. On the other hand the increasing availability a...