high performance computing on graphics processing units: hgpu.org

Data Mining algorithms such as classification and clustering are the future of computation, though multidimensional data-processing is required. People are using multicore processors with GPU’s. Most of the programming languages doesn’t provide multiprocessing facilities and hence wastage of processing resources. Clustering and classification algorithms are more resource consuming. In this paper we have shown strategies […]

Nonlinear interdependency (NLI) analysis is an effective method for measurement of synchronization among brain regions, which is an important feature of normal and abnormal brain functions. But its application in practice has long been largely hampered by the ultra-high complexity of the NLI algorithms. We developed a massively parallel approach to address this problem. The […]

Auto-tuning is a widely used and effective technique for optimizing a parametrized GPU code template for a particular computation on particular hardware. Its drawback is that thorough or exhaustive auto-tuning requires compiling many kernels and calling each one many times; this process is slow. Furthermore, library abstraction boundaries provide operations such as image filtering and […]

Determining the best set of optimizations to apply to a kernel to be executed on the graphics processing unit (GPU) is a challenging problem. There are large sets of possible optimization configurations that can be applied, and many applications have multiple kernels. Each kernel may require a specific configuration to achieve the best performance, and […]

The Finite-Difference Time-Domain (FDTD) method is a computational technique for modelling the behaviour of electromagnetic waves in three-dimensional space. When executed to solve real-world problems the FDTD method is characterised by long execution times involving a large amount of data organised into matrices. The FDTD method exhibits ample data parallelism, and parallel computing techniques are […]

In this article, a novel and systematic Low-density parity-check (LDPC) code construction, verification and implementation methodology is proposed. The methodology is composed by the simulated annealing based LDPC code constructor, the GPU based high-speed code selector, the ant colony optimization based pipeline scheduler and the FPGA-based hardware implementer. Compared to the traditional ways, this methodology […]

A novel cryptography method based on the Lorenz’s attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if […]

We present a new approach to utilizing all CPU cores and all GPUs on heterogeneous multicore and multi-GPU systems to support dense matrix computations efficiently. The main idea is that we treat a heterogeneous system as a distributed-memory machine, and use a heterogeneous multi-level block cyclic distribution method to allocate data to the host and […]

Data-parallel languages like OpenCL and CUDA are an important means to exploit the computational power of today’s computing devices. In this paper, we deal with two aspects of implementing such languages on CPUs: First, we present a static analysis and an accompanying optimization to exclude code regions from control-flow to data-flow conversion, which is the […]

With an increasing amount of data and demand for fast query processing, the efficiency of database operations continues to be a challenging task. A common approach is to leverage parallel hardware platforms. With the introduction of general-purpose GPU (Graphics Processing Unit) computing, massively parallel hardware has become available within commodity hardware. XML is based on […]

One of the principle challenges of Constraint Automata composition is the rapid growth of the state space and the diffficulty inherent in processing very large state spaces both in terms of space as well as computation time. We show that the method outlined here goes some way in tackling both these issues by making it […]

The current trend towards heterogeneous architectures requires a global rethinking of software and hardware design. The focus is centered around new parallel programming models, design space exploration and run-time resource management techniques to exploit the features of many-core processor architectures. Graphics Processing Units (GPU) have become the platform of choice in this area for accelerating […]