high performance computing on graphics processing units: hgpu.org

For some classes of problems, NVIDIA CUDA abstraction and hardware properties combine with problem characteristics to limit the specific problem instances that can be effectively accelerated. As a real-world example, a twodimensional correlation-based template-matching MATLAB application is considered. While this problem has a well known solution for the common case of linear image filtering-small fixed […]

General purpose GPU computation is a fast growing ?eld with a variety of applications. For maximum performance, though, mapping high-level parallel algorithms to vendor hardware requires a solid grasp of both the algorithm’s computational requirements and the microarchitectural limitations of the GPU. This work aims to explore the performance of high and low arithmetic intensity […]

We present FATSEA, a functional and performance evaluation simulator written in C++ to handle kernels written in the CUDA programming language aimed for GPGPU computing. FATSEA takes a Parallel Thread eXecution (PTX ) code as input, which is a device independent code format generated by the Nvidia CUDA compiler, to validate results and estimate performance […]

Parallel Thread Execution ISA (PTX) is a virtual instruction set used by NVIDIA GPUs that explicitly expresses hierarchical MIMD and SIMD style parallelism in an application. In such a programming model, the programmer and compiler are left with the not trivial, but not impossible, task of composing applications from parallel algorithms and data structures. Once […]

Inverse distance weighting (IDW) interpolation and viewshed are two popular algorithms for geospatial analysis. IDW interpolation assigns geographical values to unknown spatial points by using values from a usually scattered set of known points, and viewshed identifies the cells in a spatial raster that can be seen by observers. Although the implementations of both algorithms […]

Indexed Foreign-Key Joins expose a very asymmetric access pattern: the Foreign-Key Index is sequentially scanned whilst the Primary-Key table is target of many quasi-random lookups which is the dominant cost factor. To reduce the costs of the random lookups the fact-table can be (re-) partitioned at runtime to increase access locality on the dimension table, […]

Conventional systems based on general-purpose processors cannot keep pace with the exponential increase in the generation and collection of data. It is therefore important to explore alternative architectures that can provide the computational capabilities required to analyze ever-growing datasets. Programmable graphics processing units (GPUs) offer computational capabilities that surpass even high-end multi-core central processing units […]

Radio astronomy is a subfield of astronomy that studies celestial objects at radio frequencies. Unlike visible light, these radio signals are not blocked by earth’s atmosphere, making it possible to detect them from the ground. Radio emissions have been observed from a number of celestial bodies, including stars and galaxies. Some celestial bodies that can […]

This thesis investigates the possibility to extend the Erlang runtime system such that it can take advantage of special purpose compute units, such as GPUs and DSPs. Further more it investigates if certain parts of an Erlang system can be accelerated with help of these devices.

Differential evolution is an efficient populational meta — heuristic optimization algorithm successful in solving difficult real world problems. Due to the simplicity of its operations and data structures, it is suitable for a parallel implementation on multicore systems and on the GPU. In this paper, we design a simple yet highly parallel implementation of the […]

Modern GPUs like NVidia’s Fermi internally operate in a SIMD manner by ganging multiple (32) scalar threads together into SIMD warps; if a warp’s threads diverge, the warp serially executes both branches, temporarily disabling threads that are not on that path. In this paper, we explore and thoroughly analyze the concept of active thread compaction—i.e., […]

The tremendous computing power of Graphics Processing Units (GPUs) can be used to accelerate the evolution process in Genetic Programming (GP). The automatic generation of code using the GPU usually follows two different approaches: compiling each evolved or interpreting multiple programs. Both approaches, however, have performance drawbacks. In this work, we propose a novel approach […]