Adding fault tolerance to OpenCL: Through redundant heterogeneous computing

The ever-increasing demand for computing has led to the need for specialized heterogeneous hardware, and the frameworks required to utilize them. Besides the traditional central processing units, more and more programs will make use of specialized hardware to accelerate computations. However, the increase in computing also leads to shorter mean...

Solving convex optimization problems on FPGA using OpenCL

The application of accelerators in HPC applications has seen enormous growth in the last decade. In the field of HPC demands on throughput are steadily growing. <br/>Not all of the algorithms used have a clear HW architecture which performs the best. Our work explores the performance of different HW architectures in solving a convex optimization...

High Performance Histograms on SIMT and SIMD Architectures

Using the histogram procedure, this work studies performance determining factors in computing in parallel on SIMD and SIMT devices. Modern graphics pro-cessing units (GPUs) support SIMT, multiple threads running the same instruction, whereas central processing units (CPUs) use SIMD, in which one instruction op-erates on multiple operands. As...

An Accelerator based on the ?-VEX Processor: An Exploration using OpenCL

In recent years the use of co-processors to accelerate specific tasks is becoming more common. To simplify the use of these accelerators in software, the OpenCL framework has been developed. This framework provides programs a cross-platform interface for using accelerators. The ?-VEX processor is a run-time reconfigurable VLIW processor. It...

Speeding Up Reinforcement Learning with Graphics Processing Units

Conventionally programmed systems (e.g. robots) are not able to adapt to unforeseen changes in their task or environment. Reinforcement learning (RL), a machine learning approach, could grant this flexibility. Many fields of work could greatly benefit from this, be it in terms of cost, time or some other parameter. With RL, a learning agent...

Accelerating Protein Sequence Alignment with Different Parallel Hardware Platforms

Detecting similarities between (RNA, DNA, and protein) sequences is an important part of bioinformatics. Among the algorithms used to accomplish this, the Smith-Waterman algorithm is very popular. A sequential implementation of Smith-Waterman requires quadratic running time with respect to the length of the sequences. As the amount of data in...

A comprehensive study of Dynamic Memory Management in OpenCL kernels

Traditional (sequential) applications use malloc for a variety of dynamic data structures, like linked lists or trees. GPGPU is gaining attention and popularity because its massively-parallel architecture allows for great speed improvement for programs that can be parallelised and implemented for a platform like OpenCL. Programmers who try to...

Accelerating Graph Analysis with Heterogeneous Systems

Data analysis is a rising field of interest for computer science research due to the growing amount of information that is digitally available. This increase in data has as direct consequence that any analysis is significantly complex. By using structured representations for the data sets, like graphs, the analysis becomes feasible, but is still...

Programmability Analysis of Image Processing Kernels on Multi-/Many-core Platforms

In the last few years, the computing industry has changed its course from ever higher clock speeds to multi- and many-core systems. These new parallel systems su?er a “programmability gap”: there is a large gap between the performance a platform is theoretically capable of, and what the programmer is able to achieve. Early programming models...

An OpenCL-based Solution for Portable Bodyscan SAR Processing on Multicore Platforms

Multicore systems have become an indispensable part of our everyday life. They represent a viable alternative for increasing processor performance without hitting the memory and power walls. However, the shift from traditional programming to multicore programming has a critical influence in three dimensions: the applications, the software tools,...