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Posts

Sep, 16

High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing

High-accuracy optimization is the key component of time-sensitive applications in computer sciences such as machine learning, and we develop single-GPU Iterative Discrete Approximation Monte Carlo Optimization (IDA-MCS) and multi-GPU IDA-MCS in our previous research. However, because of the memory capability constrain of GPUs in a workstation, single-GPU IDA-MCS and multi-GPU IDA-MCS may be in low […]
Sep, 16

Performance analysis of a 240 thread tournament level MCTS Go program on the Intel Xeon Phi

In 2013 Intel introduced the Xeon Phi, a new parallel co-processor board. The Xeon Phi is a cache-coherent many-core shared memory architecture claiming CPU-like versatility, programmability, high performance, and power efficiency. The first published micro-benchmark studies indicate that many of Intel’s claims appear to be true. The current paper is the first study on the […]
Sep, 16

Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a beam of streaming particles to be intercepted and hit by an ultrashort high energy X-ray beam. Through machine learning methods the data thus […]
Sep, 15

Exploratory Data Analysis of Software Repositories via GPU Processing

Analyzing software repositories with thousands of artifacts is data intensive, which makes interactive exploration analysis of such data infeasible. We introduce a novel approach, Dominoes, that can support automated exploration of relationships amongst project elements, where users have the flexibility to explore on the fly the numerous types of project relationships. Dominoes organizes data extracted […]
Sep, 15

Interactive Wave Simulations

Simulation of ocean waves can be categorized into two major groups. First one is based on the physical models whereas the other generates the ocean waves based on either geometrical shapes or oceanography spectrums. Even though the later method group requires less computational effort, the waves modelled are less realistic in nature. Currently MARIN (Maritime […]
Sep, 15

Scalable Multi-GPU Simulation of Long-Range Molecular Dynamics

Molecular dynamics simulations allow us to study the behavior of complex biomolecular systems by modeling the pairwise interaction forces between all atoms. Molecular systems are subject to slowly decaying electrostatic potentials, which turn molecular dynamics into an n-body problem. In this paper, we present a parallel and scalable solution to compute long-range molecular forces, based […]
Sep, 15

Accelerated Variance Reduction Methods on GPU

Monte Carlo simulations have become widely used in computational finance. Standard error (SE in short) is the basic notion to measure the quality of a Monte Carlo estimator, and the square of SE is defined as the variance divided by the total number of simulations. Variance reduction methods have been developed as efficient algorithms by […]
Sep, 15

Scalable Parallel Tridiagonal Algorithms with Diagonal Pivoting and Their Optimization for Many-Core Architectures

Tridiagonal solvers are important building blocks for a wide range of scientific applications that are commonly performance-sensitive. Recently, many-core architectures, such as GPUs, have become ubiquitous targets for these applications. Therefore, a high-performance general-purpose GPU tridiagonal solver becomes critical. However, no existing GPU tridiagonal solver provides comparable quality of solutions to most common, general-purpose CPU […]
Sep, 13

Parallel Computation of Non-Bonded Interactions in Drug Discovery: Nvidia GPUs vs. Intel Xeon Phi

Currently, medical research for the discovery of new drugs is increasingly using Virtual Screening (VS) methods. In these methods, the calculation of the non-bonded interactions, such as electrostatic or van der Waals, plays an important role, representing up to 80% of the total execution time. These are computationally intensive operations, and massively parallel in nature, […]
Sep, 13

Parallel CYK Membership Test on GPUs

Nowadays general-purpose computing on graphics processing units (GPGPUs) performs computations what were formerly handled by the CPU using hundreds of cores on GPUs. It often improves the performance of sequential computation when the running program is well-structured and formulated for massive threading. The CYK algorithm is a well-known algorithm for the context-free language membership test […]
Sep, 13

Analysis of GPU-based convolution for acoustic wave propagation modeling with finite differences: Fortran to CUDA-C step-by-step

By projecting observed microseismic data backward in time to when fracturing occurred, it is possible to locate the fracture events in space, assuming a correct velocity model. In order to achieve this task in near real-time, a robust computational system to handle backward propagation, or Reverse Time Migration (RTM), is required. We can then test […]
Sep, 13

Performance and Power Optimization of GPU Architectures for General-purpose Computing

Power-performance efficiency has become a central focus that is challenging in heterogeneous processing platforms as the power constraints have to be established without hindering the high performance. In this dissertation, a framework for optimizing the power and performance of GPUs in the context of general-purpose computing in GPUs (GPGPU) is proposed. To optimize the leakage […]

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