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Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. As an obstacle to widespread adoption, programming GPUs has remained difficult due to the need of using low-level control of the hardware to achieve good performance. This paper suggests a programming […]
Marwan Abdellah
For embarrassingly parallel algorithms, a Graphics Processing Unit (GPU) outperforms a traditional CPU on price-per-flop and price-per-watt by at least one order of magnitude. This had led to the mapping of signal and image processing algorithms, and consequently their applications, to run entirely on GPUs. This paper presents CUFFTSHIFT, a ready-to-use GPU-accelerated library, that implements […]
Felix Weninger, Johannes Bergmann, Bjorn Schuller
In this article, we introduce CURRENNT, an open-source parallel implementation of deep recurrent neural networks (RNNs) supporting graphics processing units (GPUs) through NVIDIA’s Computed Unified Device Architecture (CUDA). CURRENNT supports uni- and bidirectional RNNs with Long Short-Term Memory (LSTM) memory cells which overcome the vanishing gradient problem. To our knowledge, CURRENNT is the first publicly […]
Bruce Merry
Sorting and scanning are two fundamental primitives for constructing highly parallel algorithms. A number of libraries now provide implementations of these primitives for GPUs, but there is relatively little information about the performance of these implementations. We benchmark seven libraries for 32-bit integer scan and sort, and sorting 32-bit values by 32-bit integer keys.We show […]
Changsheng Huang, Baochang Shi, Zhaoli Guo, Zhenhua Chai
Conducting lattice Boltzmann method on GPU has been proved to be an effective manner to gain a significant performance benefit, thus the GPU or multi-GPU based lattice Boltzmann method is considered as a promising and competent candidate in the study of large-scale complex fluid flows. In this work, a multi-GPU based lattice Boltzmann algorithm coupled […]
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Ahmad Abdelfattah, David Keyes, Hatem Ltaief
KBLAS is a new open source high performance library that provides optimized kernels for a subset of Level 2 BLAS functionalities on CUDA-enabled GPUs. Since performance of dense matrix-vector multiplication is hindered by the overhead of memory accesses, a double-buffering optimization technique is employed to overlap data motion with computation. After identifying a proper set […]
Di Wu, Ling Shao
The purpose of this paper is to describe a novel method called Deep Dynamic Neural Networks(DDNN) for the Track 3 of the Chalearn Looking at People 2014 challenge [1]. A generalised semi-supervised hierarchical dynamic framework is proposed for simultaneous gesture segmentation and recognition taking both skeleton and depth images as input modules. First, Deep Belief […]
Lukas Machlica, Jan Vanek, Zbynek Zajıc
Gaussian Mixture Models (GMMs) are widely used among scientists e.g. in statistics toolkits and data mining procedures. In order to estimate parameters of a GMM the Maximum Likelihood (ML) training is often utilized, more precisely the Expectation-Maximization (EM) algorithm. Nowadays, a lot of tasks works with huge datasets, what makes the estimation process time consuming […]
Weibin Sun
As the base of the software stack, system-level software is expected to provide efficient and scalable storage, communication, security and resource management functionalities. However, there are many computationally expensive functionalities at the system level, such as encryption, packet inspection, and error correction. All of these require substantial computing power. What’s more, today’s application workloads have […]
Dinghua Li, Chi-Man Liu, Ruibang Luo, Kunihiko Sadakane, Tak-Wah Lam
MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252Gbps in 44.1 hours and 99.6 hours on a single computing node with and without a GPU, respectively. MEGAHIT assembles the data as a whole, i.e., it […]
Romain Dolbeau
This paper describes & evaluates a fast, hybrid implementation of the Advanced Encryption Standard with 256 bit keys (AES-256) block encryption in Galois/Counter Mode (GCM). The implementation is bit-compatible with the implemented standard in both the OpenSSL and Crypto++ libraries, while significantly (up to three times) faster for large amount of data. In this implementation, […]
Jukka Saarelma, Lauri Savioja
Wave based simulation methods have been utilized to numerically estimate wave propagation in domains where low-frequency wave effects dominate the response. Finite-difference time-domain (FDTD) methods are increasingly useful for such problems, but they require massive spatial oversampling to increase the bandwidth of the simulation, which leads to significant computational expense. The advantage of explicit time-stepping […]
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