high performance computing on graphics processing units: hgpu.org

BACKGROUND: Visualization of multi-channel microscopy data plays a vital role in biological research. With the ever-increasing resolution of modern microscopes the data set size of the scanned specimen grows steadily. On commodity hardware this size easily exceeds the available main memory and the even more limited GPU memory. Common volume rendering techniques require the entire […]

The road towards Exascale Computing requires a holistic effort to address three different challenges simultaneously: high performance, energy efficiency, and programmability. The use of runtime task schedulers to orchestrate parallel executions with minimal developer intervention has been introduced in recent years to tackle the programmability issue while maintaining, or even improving, performance. In this paper, […]

The numerical solution of partial differential equations using the finite element method is one of the key applications of high performance computing. Local assembly is its characteristic operation. This entails the execution of a problem-specific kernel to numerically evaluate an integral for each element in the discretized problem domain. Since the domain size can be […]

Random Field (RF) generation algorithms are of paramount importance for many scientific domains, such as astrophysics, geostatistics, computer graphics and many others. Some examples are the generation of initial conditions for cosmological simulations or hydrodynamical turbulence driving. In the latter a new random field is needed every time-step. Current approaches commonly make use of 3D […]

Graph is a widely used data structure and graph algorithms, such as breadth-first search (BFS), are regarded as key components in a great number of applications. Recent studies have attempted to accelerate graph algorithms on highly parallel graphics processing unit (GPU). Although many graph algorithms based on large graphs exhibit abundant parallelism, their performance on […]

CONTEXT: Reinforcement Learning (RL) is a time consuming effort that requires a lot of computational power as well. There are mainly two approaches to improving RL efficiency, the theoretical mathematics and algorithmic approach or the practical implementation approach. In this study, the approaches are combined in an attempt to reduce time consumption. OBJECTIVES: We investigate […]

Pattern matching is a highly computationally intensive operation used in SNORT system but due to the increasingly storage capacity and the link speed the amount of data that need to be match against pattern is increased rapidly and traditional system is fail to match that data. GPU Computing Have attracted lots of attention due to […]

CONTEXT: Procedural Terrain Generation refers to the algorithmical creation of terrains with limited or no user input. Terrains are an important piece of content in many video games and other forms of simulations. OBJECTIVES: In this study a tile-based approach to creating endless terrains is investigated. The aim is to find if real-time performance is […]

The scope of this research paper is one very important aspects nowadays, the security and management of one of the most important services the email and all of the alike online services today. This paper attempts to investigate the possible benefits of using standard signature-driven spam detection logic in combination with algorithm for network intrusion […]

Modern-day computer security relies heavily on cryptography as a means to protect the data that we have become increasingly reliant on. The main research in computer security domain is how to enhance the speed of RSA algorithm. The computing capability of Graphic Processing Unit as a co-processor of the CPU can leverage massive-parallelism. This paper […]

Matrix multiplication is a fundamental linear algebra routine ubiquitous in all areas of science and engineering. Highly optimised BLAS libraries (cuBLAS and clBLAS on GPUs) are the most popular choices for an implementation of the General Matrix Multiply (GEMM) in software. However, performance of library GEMM is poor for small matrix sizes. In this thesis […]

The examination timetabling problem belongs to the class of combinatorial optimization problems and is of great importance for every University. In this paper, a hybrid evolutionary algorithm running on a GPU is employed to solve the examination timetabling problem. The hybrid evolutionary algorithm proposed has a genetic algorithm component and a greedy steepest descent component. […]