high performance computing on graphics processing units: hgpu.org

This master thesis focuses on several high-level parallel programming models for heterogeneous systems that have been becoming increasingly popular in the field of high-performance computing. Heterogeneous systems are an inexpensive and effective way for further performance improvements. A powerful combination of graphics processing units (GPUs) and central processing units (CPUs) is one of the most […]

Heterogeneous systems are becoming increasingly common. Relatedly, the popularity of OpenCL is growing, as it provides a unified mean to program a wide variety of devices including GPUs or multicore CPUs. More recently, the Heterogeneous Programming Library (HPL) targets the same variety of systems as OpenCL, intending to improve their programmability. The main drawback of […]

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements […]

Embedded graphic processing unit (GPU) accelerates a real-time rendering process of a graphics application on mobile devices, however, at the cost of consuming a considerable portion of the system energy [1] which is one of the most critical design issues for battery-operated devices. To estimate the power consumption of a graphics application, conventional approaches collect […]

DEFG is our declarative language and framework for the efficient generation of OpenCL GPU applications. Using our new DEFG implementation, run-time and lines-of-code comparisons are provided for three well-known algorithms: Sobel image filtering, breadth-first search and all-pairs shortest path. The DEFG declarative language and corresponding OpenCL kernels provide complete OpenCL applications. The lines-of-code comparison demonstrates […]

We study static timing analysis of programs running on GPU accelerators. Such programs follow a data parallel programming model that allows massive parallelism on manycore processors. Data parallel programming and GPUs as accelerators have received wide use during the recent years. The timing analysis of programs running on single core machines is well known and […]

Metaheuristics is a class of approximate methods based on heuristics that can effectively handle real world (usually NP-hard) problems of high-dimensionality with multiple objectives. An existing multi-objective Tabu-Search (MOTS2) has been re-designed by and ported onto Compute Unified Device Architecture (CUDA) so as to effectively deal with a scalable multi-objective problem with a range of […]

In this paper we have proposed parallel implementation of Ant colony optimization Ant System algorithm on GPU using OpenCL. We have done comparison on different parameters of the ACO which directly or indirectly affect the result. Parallel comparison of speedup between CPU and GPU implementation is done with a speed up of 3.11x in CPU […]

In this paper, we discuss an efficient implementation of the three-dimensional multigrid Poisson solver on a many-core coprocessor, Intel Xeon Phi. We have used the modified block red-black (mBRB) Gauss-Seidel (GS) smoother to achieve sufficient degree of parallelism and high cache hit ratio. We have vectorized (SIMDized) the GS steps in the smoother by introducing […]

Graphics processing units (GPUs) provide orders-of-magnitude speedup for compute-intensive data-parallel applications. However, enterprise and cloud computing domains, where resource isolation of multiple clients is required, have poor access to GPU technology. This is due to lack of operating system (OS) support for virtualizing GPUs in a reliable manner. To make GPUs more mature system citizens, […]

In driving assistance system (DAS), road marking’s data can provide important assistance for driving safety. As the input image usually includes unnecessary information, lane detection system usually needs to remove most unnecessary data except for the lane markings. In this paper, a road marking extraction method is proposed to separate the painted lane lines using […]

The exponential growth in bioinformatics data generation and the stagnation of processor frequencies in modern processors stress the need for efficient implementations that fully exploit the parallel capabilities offered by modern computers. This thesis focuses on parallel algorithms and implementations for bioinformatics problems. Various types of parallelism are described and exploited. This thesis presents applications […]