ArrayFire v2.0
17 December 2013
ArrayFire has announced the release of ArrayFire v2.0
The automotive sector is undergoing a period of rapid and disruptive transformation from both a business and technical standpoint.
AccelerEyes
ArrayFire for Intel Xeon Phi
29 November 2012
AccelerEyes has announced the latest release of ArrayFire, adding support for the new Intel Xeon Phi coprocessors
Jacket v2.1
22 May 2012
AccelerEyes rolls up sleeves with new Jacket
Jacket v2.0
12 December 2011
AccelerEyes has released v2.0 of Jacket, adding GPU computing capabilities for use with Matlab. The latest version delivers even more speed through a host of new improvements, maximising GPU device performance and utilisation
ArrayFire
23 November 2011
AccelerEyes has launched ArrayFire, a freely-available GPU software library supporting Cuda and OpenCL devices
LibJacket v1.0
7 June 2011
AccelerEyes has released version 1.0 of LibJacket, enabling programmers to achieve better GPU performance with less programming
Jacket v1.7
22 March 2011
AccelerEyes has released version 1.7 of its Jacket software for GPU computing with Matlab
Jacket v1.5
28 September 2010
AccelerEyes has released version 1.5 of Jacket, its GPU programming platform for Matlab
Jacket 1.4
12 August 2010
AccelerEyes has released version 1.4 of its Jacket software platform for Matlab, adding support the latest Nvidia GPUs based on the Fermi architecture
Jacket version 1.3
16 April 2010
AccelerEyes has introduced version 1.3 of its Jacket GPU computing software that integrates double precision linear algebra, is easier to setup, performs faster, and is less expensive
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Estimates suggest that the global laboratory informatics market, valued at $2.6 billion in 2019, will witness CAGR of 7.5 per cent over the next five years, reaching $3.8 billion in 2024[1].
Modern drug discovery and development workflows incorporate a growing range of automated, high-throughput technologies that can generate data on a truly impressive scale.
‘This will be the life sciences century … because of personalised medicine, information technology, and knowledge on biological systems,’ said Fred Hassan, a partner of Warburg Pincus and former CEO of Schering-Plough.
With data rates increasing and more complex challenges arising in life sciences, Panasas’ Jim Donovan and Dale Brantly discuss the benefits of using HPC for these workloads
As the complexity of both HPC hardware and the challenges that scientists are trying to solve using HPC systems increases, ensuring a system is utilised efficiently is necessary to deliver a computing service with value for money and a high research output.
Architectural specialisation is one option to continue to improve performance beyond the limits imposed by the slow down in Moore’s Law.
As not only the HPC industry but the larger computing ecosystem tries to overcome the slowdown and eventual end of transistor scaling described by Moore’s Law, scientists and researchers are implementing programmes that will define the technologies and new materials needed to supplement, or repla
