high performance computing on graphics processing units: hgpu.org

In this thesis, the performance and energy efficiency of four different implementations of matrix multiplication, written in OmpSs and OpenCL, is tested and evaluated. The benchmarking is done using an Intel Ivy Bridge Core i7 3770K. The results are evaluated and discussed with regards to different optimization configurations, like vectorization and multi-threading. Energy measurements are […]

Graph algorithms play a prominent role in several fields of sciences and engineering. Notable among them are graph traversal, finding the connected components of a graph, and computing shortest paths. There are several efficient implementations of the above problems on a variety of modern multiprocessor architectures. It can be noticed in recent times that the […]

Multiplying a sparse matrix with a vector, denoted spmv, is a fundamental operation in linear algebra with several applications. Hence, efficient and scalable implementation of spmv has been a topic of immense research. Recent efforts are aimed at implementations on GPUs, multicore architectures, and such emerging computational platforms. Owing to the highly irregular nature of […]

A variety of hardware platforms for signal processing has emerged, from distributed systems such as Wireless Sensor Networks (WSNs) to parallel systems such as Multicore Programmable Digital Signal Processors (PDSPs), Multicore General Purpose Processors (GPPs), and Graphics Processing Units (GPUs) to heterogeneous combinations of parallel and distributed devices. When a signal processing application is implemented […]

Over the past decade, soft microprocessors and vector processors have been extensively used in FPGAs for a wide variety of applications. However, it is difficult to straightforwardly extend their functionality to support conditional and thread-based execution characteristic of general-purpose graphics processing units (GPGPUs) without recompiling FPGA hardware for each application. In this paper, we describe […]

Graphics Processing Units (GPUs) have emerged as highly capable computational accelerators for scientific and engineering applications. Many reports claim orders of magnitude of speedup compared to traditional Central Processing Units (CPUs), and the interest for GPU computation is high in the computational world. In this thesis, the capability of using GPUs to accelerate the full […]

The Jacobian evaluation problem is ubiquitous throughout scientiOc computing. In this article, the possibility of massively parallel computing of Jacobian matrix is discussed. It is shown that the computation of the Jacobian matrix shares the same parallelism with the computation being differentiated, which suggests that once we know how to parallelize a computation, its Jacobian […]

OpenCL programming provides full code portability between different hardware platforms, and can serve as a good programming candidate for heterogeneous systems, which typically consist of a host processor and several accelerators. However, to make full use of the computing capacity of such a system, programmers are requested to manage diverse OpenCL-enabled devices explicitly, including distributing […]

At present, NVIDIA’s CUDA can support programmers to develop highly parallel applications. It utilizes some parallel construct concepts: hierarchical thread blocks, shared memory, and barrier synchronization. CUDA development programs can be used to achieve amazing acceleration. The graphics processor is able to play an important role in cloud computing in a cluster environment, because it […]

This work aims to enable Swift to efficiently use accelerators (such as NVIDIA GPUs) to further accelerate a wide range of applications. This work presents preliminary results in the costs associated with managing and launching concurrent kernels on NVIDIA Kepler GPUs. We expect our results to be applicable to several XSEDE resources, such as Forge, […]

Spatial data mining techniques enable the knowledge extraction from spatial databases. However, the high computational cost and the complexity of algorithms are some of the main problems in this area. This work proposes a new algorithm referred to as VDBSCAN+, which derived from the algorithm VDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise) […]

Physically based rendering using ray tracing is capable of producing realistic images of much higher quality than other methods. However, the computational costs associated with exploring all paths of light are huge; it can take hours to render high quality images of complex scenes. Using graphics processing units has emerged as a popular way to […]