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Posts

Mar, 22

A Survey of Techniques for Architecting and Managing GPU Register File

To support their massively-multithreaded architecture, GPUs use very large register file (RF) which has a capacity higher than even L1 and L2 caches. In total contrast, traditional CPUs use tiny RF and much larger caches to optimize latency. Due to these differences, along with the crucial impact of RF in determining GPU performance, novel and […]
Mar, 20

OpenCL Cryptographic Library

Modern GPUs are devices with very high parallelism for a very low cost. Integer and logic instruction support enable us to use them for many workloads unrelated to rendering. Cryptographic algorithms like AES or Blowfish can benefit from being executed on the system’s GPU. Such execution off-loads work from the main CPU, freeing it to […]
Mar, 20

Automatic Detection and Denoising of Signals in Large Geophysical Datasets

To fully understand the complex interactions of various phenomena in the natural world, scientific disciplines such as geology and seismology increasingly rely upon analyzing large amounts of observations. However, data collection is growing at a faster rate than what is currently possible to analyze through traditional approaches. These datasets, supplied by the increasing use of […]
Mar, 20

Acceleration of ensemble machine learning methods using many-core devices

We present a case study into the acceleration of ensemble machine learning methods using many-core devices in collaboration with Toshiba Medical Visualisation Systems Europe (TMVSE). The adoption of GPUs to execute a key algorithm in the classification of medical image data was shown to significantly reduce overall processing time. Using a representative dataset and pre-trained […]
Mar, 20

A Massively Parallel Algorithm for Cell Classification Using CUDA

In Bioinformatics, cell classification is the act of separating human cells into different groups based on their RNA-seq expression levels. These data can be quite large, as there are about 20,000 known human genes. Even relatively small datasets (< 1000 cell samples) can contains millions of values. Computations and classifications on this data force a […]
Mar, 20

Analyzing and Improving the Performance of Spatial Database Processing

Spatial databases have become increasingly important, due to the advent of popular geospatial Web services such as Google Maps, GPS navigation systems, and a host of accompanying location-based services. Spatial databases are used in a variety of real-world applications involving complex data analytics: land surveying, urban planning, environmental assessments, or new BigData application domains like […]
Mar, 18

4th International Workshop on OpenCL (IWOCL), 2016

There is a great program lined up for IWOCL 2016 in Vienna this April 19-21: IWOCL 2016 Sessions The 10% early bird registration discount ends March 20th, so don’t delay, register today!
Mar, 15

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Breakthroughs from the field of deep learning are radically changing how sensor data are interpreted to extract the high-level information needed by mobile apps. It is critical that the gains in inference accuracy that deep models afford become embedded in future generations of mobile apps. In this work, we present the design and implementation of […]
Mar, 15

DySel: Lightweight Dynamic Selection for Kernel-based Data-parallel Programming Model

The rising pressure for simultaneously improving performance and reducing power is driving more diversity into all aspects of computing devices. An algorithm that is wellmatched to the target hardware can run multiple times faster and more energy efficiently than one that is not. The problem is complicated by the fact that a program’s input also […]
Mar, 15

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

The current trend in next-generation exascale systems goes towards integrating a wide range of specialized (co-)processors into traditional supercomputers. However, the integration of different specialized devices increases the degree of heterogeneity and the complexity in programming such type of systems. Due to the efficiency of heterogeneous systems in terms of Watt and FLOPS per surface […]
Mar, 15

Melia: A MapReduce Framework on OpenCL-based FPGAs

MapReduce, originally developed by Google for search applications, has recently become a popular programming framework for parallel and distributed environments. This paper presents an energy-efficient architecture design for MapReduce on Field Programmable Gate Arrays (FPGAs). The major goal is to enable users to program FPGAs with simple MapReduce interfaces, and meanwhile to embrace automatic performance […]
Mar, 15

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Matrix factorization (MF) is employed by many popular algorithms, e.g., collaborative filtering. The emerging GPU technology, with massively multicore and high intra-chip memory bandwidth but limited memory capacity, presents an opportunity for accelerating MF much further when appropriately exploiting the GPU architectural characteristics. This paper presents cuMF, a CUDA-based matrix factorization library that implements memory-optimized […]
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