high performance computing on graphics processing units: hgpu.org

Modern GPUs (Graphics Processing Units) are becoming more relevant in the world of HPC (High Performance Computing) thanks to their large computing power and relative low cost, however their special architecture results in more complex programming. To take advantage of their computing resources and develop efficient implementations is essential to have certain knowledge about the […]

Tuning code for GPGPU and other emerging many-core platforms is a challenge because few models or tools can precisely pinpoint the root cause of performance bottlenecks. In this paper, we present a performance analysis framework that can help shed light on such bottlenecks for GPGPU applications. Although a handful of GPGPU profiling tools exist, most […]

Multicore machines equipped with accelerators are becoming increasingly popular in the High Performance Computing ecosystem. Hybrid architectures provide significantly improved energy efficiency, so that they are likely to generalize in the Manycore era. However, the complexity introduced by these architectures has a direct impact on programmability, so that it is crucial to provide portable abstractions […]

This thesis deals with code generation for parallel applications on emerging platforms, in particular FPGA and GPU-based platforms. These platforms expose a large design space, throughout which performance is affected by significant architectural idiosyncrasies. In this context, generating efficient code is a global optimization problem. The code generation methods described in this thesis apply to […]

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 […]