ArrayFire has announced the release of ArrayFire v2.0
AccelerEyes has announced the latest release of ArrayFire, adding support for the new Intel Xeon Phi coprocessors
AccelerEyes rolls up sleeves with new Jacket
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
AccelerEyes has launched ArrayFire, a freely-available GPU software library supporting Cuda and OpenCL devices
AccelerEyes has released version 1.0 of LibJacket, enabling programmers to achieve better GPU performance with less programming
AccelerEyes has released version 1.7 of its Jacket software for GPU computing with Matlab
AccelerEyes has released version 1.5 of Jacket, its GPU programming platform for Matlab
AccelerEyes has released version 1.4 of its Jacket software platform for Matlab, adding support the latest Nvidia GPUs based on the Fermi architecture
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
Through the use of cutting-edge simulation, software engineers are developing innovative new wind energy technology and increasing the efficiency and durability of wind turbines. The drive to find sustainable energy sources is one of the most pressing concerns facing society.
Dame Sally Davies, the outgoing Chief Medical Officer for England, pulls no punches when it comes to the threat of antibiotic resistance. She has called for an ‘Extinction Rebellion-type’ response to it, describing it as ‘catastrophic’ and ‘as dangerous as climate change’.
The Pistoia Alliance has been pioneering initiatives that will support organisations as they work to enable and engage Fair (findable, accessible, interoperable, reusable) principles of data management and stewardship in their organisations.
Achronix and Bittware collaborate on a new FPGA designed for cloud, AI and machine learning applications, writes Robert Roe
By increasing the energy efficiency of a supercomputer scientists can save huge amounts of money over the total lifecycle of the system. With ever-increasing core counts and increasingly large supercomputers, the drive for increased computational power comes at a cost.
