Application Time vs Solver Time

August 24, 2013

Last week, HPCwire ran an interesting article entitled, “Where has HPC’s math gone?” The article analyzes the increasing importance of math solvers to successful HPC outcomes. As the number of cores grows, the percentage of time HPC codes spend in solvers increases significantly. The following chart illustrates this trend nicely:   ArrayFire is ideally suited […]

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clMath: An Open Source BLAS and FFT Library for OpenCL

August 13, 2013

If you’re reading our blog, BLAS and FFT libraries likely form an important basis for your work. For instance, BLAS and FFT libraries are used in some of ArrayFire’s higher-level functions for linear algebra, signal processing, and image processing. Today, OpenCL is getting a big boost in BLAS and FFT library availability. AMD has announced a […]

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ArrayFire Examples (Part 7 of 8) – PDE

July 3, 2013

This is the seventh in a series of posts looking at our current ArrayFire examples. The code can be compiled and run from arrayfire/examples/ when you download and install the ArrayFire library. Today we will discuss the examples found in the pde/ directory. In these examples, my machine has the following configuration: ArrayFire v1.9.1 (build XXXXXXX) by AccelerEyes (64-bit Linux) License: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX […]

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ISC 2013 Keynote by Stephen Pawlowski of Intel

June 18, 2013

Stephen Pawlowski of Intel gave an interesting keynote today at ISC 2013. He continued the theme of yesterday’s keynote to address challenges our market faces in getting to exascale computing. Here is a summary of the points he made during his talk: Getting to exascale by 2020 requires performance improvement of 2x every year Innovations […]

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ISC 2013 Keynote by Bill Dally of NVIDIA

June 17, 2013

Bill Dally of NVIDIA gave a wonderful keynote today at ISC 2013. He focused on addressing the challenges facing our market in getting to exascale computing. He talked about how Moore’s law is alive and well because transistors continue to double at an astonishing rate. However, the additional transistors are not translating into the same […]

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ArrayFire Examples (Part 6 of 8) – Multiple GPUs

June 12, 2013

This is the sixth in a series of posts looking at our current ArrayFire examples. The code can be compiled and run from arrayfire/examples/ when you download and install the ArrayFire library. Today we will discuss the examples found in the multi_gpu/ directory. In these examples, my machine has the following configuration: ArrayFire v1.9.1 (build XXXXXXX) by AccelerEyes (64-bit Linux) License: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX […]

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ArrayFire Examples (Part 5 of 8) – Machine Learning

June 5, 2013

This is the fifth in a series of posts looking at our current ArrayFire examples. The code can be compiled and run from arrayfire/examples/ when you download and install the ArrayFire library. Today we will discuss the examples found in the machine_learning/ directory. In these examples, my machine has the following configuration: ArrayFire v1.9 (build XXXXXXX) by AccelerEyes (64-bit Mac OSX) License: […]

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Solution to NVIDIA Toolkit Installation Error for Ubuntu 12.10
[Driver: Installation Failed]

May 20, 2013

Driver: Installation Failed   You may find this error message while trying to set up the NVIDIA CUDA Toolkit in Ubuntu. I found it when I was installing the toolkit for ArrayFire   [1] CUDA Toolkit Installation 1. Download the CUDA Toolkit in the link.  2. Extract the .run file in a location sudo sh cuda_5.0.35_linux_64_ubuntu11.10-1.run […]

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Beamforming with ArrayFire

May 7, 2013

Alessandro Savoia and researchers at Università degli Studi Roma Tre have achieved an order of magnitude improvement in the performance of a beamforming application using ArrayFire for GPU acceleration with CUDA-capable NVIDIA GPUs. This application involves conventional beamforming. Steps include the application of a time delay to each signal vector, summation across all vectors, and processing on the […]

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Are You Getting Left Behind?

May 1, 2013

HPCwire posted a nice article today with trends from IDC on computer processing. These trends fall inline and corroborate things we’ve been saying here on this blog. Accelerators (including GPUs and co-processors) are taking off. Are you getting left behind? If you’re reading this blog, you’re probably at the bleeding edge, but nonetheless here are […]

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