high performance computing on graphics processing units: hgpu.org

Traditional trace-driven memory system simulation is a very time consuming process while the advent of multi-cores simply exacerbates the problem. We propose a framework for accelerating trace-driven multi-core cache simulations by utilizing the capabilities of the modern many-core Graphic Processing Units (GPUs). A straightforward way towards this direction is to rely on the inherent parallelism […]

In practice, combinatorial optimization problems are complex and computationally time-intensive. Local search algorithms are powerful heuristics which allow to significantly reduce the computation time cost of the solution exploration space. In these algorithms, the multi-start model may improve the quality and the robustness of the obtained solutions. However, solving large size and time-intensive optimization problems […]

Ultra high density oligonucleotide micro arrays allow several millions of genetic markers in a single experiment to be observed. Current bioinformatics software for gene expression quantile data normalization is unable to process such huge datasets. In parallel with this perception, the huge volume of molecular data produced by current high-throughput technologies in modern molecular biology […]

This report describes a new dataflow-based technology and associated design tools for high-productivity design, analysis, and optimization of layered sensing software for signal processing systems. Our approach provides novel capabilities, based on the principles of task-level dataflow analysis, for exploring and optimizing interactions across application behavior; operational context; high performance embedded processing platforms, and implementation […]

The increasing computational needs of parallel applications inevitably require portability across popular parallel architectures, which are becoming heterogeneous. The lack of a common parallel framework results in divergent code bases, difficulty in porting, higher maintenance cost, and, thus difficulty achieving optimal performance on target architectures. Our paper examines two representative parallel applications and describes code […]

The interplay between quantum Hall states and Cooper pairs is usually hindered by the suppression of the superconducting state due to the strong magnetic fields needed to observe the quantum Hall effect. From this point of view graphene is special since it allows the creation of strong pseudo-magnetic fields due to strain. We show that […]

In this paper, we present a runtime compilation and tuning framework for parallel programs. We extend our prior work on our auto-tuner, Active Harmony, for tunable parameters that require code generation (for example, different unroll factors). For such parameters, our auto-tuner generates and compiles new code on-the-fly. Effectively, we merge traditional feedback directed optimization and […]

In this paper, we discuss networking issues arising in the design, analysis and use for scientific computing of clusters equipped with graphics processing units. The adoption of graphics accelerators in clusters used for high-performance scientific computing is a fairly recent phenomenon and promises to be an important trend now and into the foreseeable future. After […]

The sparse matrix vector product (SpMV) is a key operation in engineering and scientific computing and, hence, it has been subjected to intense research for a long time. The irregular computations involved in SpMV make its optimization challenging. Therefore, enormous effort has been devoted to devise data formats to store the sparse matrix with the […]

This paper addresses the gap between envisioned hardware-virtualized techniques for GPU programming and a conventional approach from the point of view of an application engineer taking software engineering aspects like maintainability, understandability and productivity, and resulting achieved gain in performance and scalability into account. This gap is discussed on the basis of use cases from […]

PURPOSE: Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow’s reconstruction hardware (CPU and GPU) that allows implementing […]

With the rapid growth of network technologies, many new web services have been developed to provide various applications and computing functions. These services rely deeply on the internet. Therefore, packet classification is an important issue of network security that typically adopts a flexible packet filtering system to classify each processed packet. Traditional packet classification requires […]