Hardware news tagged GPGPU
Tuesday, November 19, 2013
IBM and Nvidia Team Up to Accelerate Corporate Data Center Applications and Next-Generation Supercomputers with Tesla Accelerators.
Companies Tap GPU-Enabled Supercomputing to Analyze Enterprise Data on the Fly
Monday, November 18, 2013
Khronos Finalizes OpenCL 2.0 Specification for Heterogeneous Computing.
OpenCL 2.0 Brings A Set of New GPGPU Capabilities
Nvidia Tesla K40 Doubles Memory of Its Predecessor, Enabling New Categories of Accelerated Applications
Sunday, November 17, 2013
Asrock Unleashes Mainboards for Bitcoin Mining.
Asrock Means Business: Reveals H81 Pro BTC & H61 Pro BTC “Mining Machines”
Thursday, November 14, 2013
Nvidia’s Cuda 6 Brings Support for Unified Memory, Multi-GPU Scaling, Drop-In Libraries.
Nvidia Simplifies Parallel Programming With Cuda 6 Platform
Tuesday, October 29, 2013
Heterogeneous Computing and 64-Bit Processing – New Trends for Mobile Devices.
GPGPU and 64-Bit Technologies to Quickly Gain Adoption in Mobile Devices
Thursday, September 12, 2013
AMD Teams Up with Adobe to Accelerate Key Content Creation Programs with GPGPU Technology.
AMD-Adobe Collaboration Unlocks Speed for Video Pros Everywhere
Wednesday, August 7, 2013
Ex-Nvidia Executive: CUDA and PhysX Are Doomed!
Roy Taylor Condemns Proprietary Technologies
Monday, July 22, 2013
Khronos Group Unveils OpenCL 2.0 Specification.
Khronos Updates OpenCL Spec to Version 2.0
Wednesday, July 3, 2013
Intel’s Next-Gen Xeon Phi “Knights Landing” to Deliver Up to 3TFLOPS of DP Performance.
Intel’s Future “Knights Landing” to Radically Boost Compute Performance
Monday, July 1, 2013
Nvidia Tesla Powers World's Most Energy Efficient Supercomputer.
Nvidia Kepler Dominates Green500 List of Energy-Efficient Supercomputer
Saturday, June 22, 2013
Low-Performance of AMD Microprocessors May Be Conditioned by… Poor BIOS.
Finnish Enthusiast Manages to Boost AMD Piledriver SuperPi Score by Tweaking the BIOS
Wednesday, June 19, 2013
Researchers Deploy GPUs to Build World's Largest Artificial Neural Network.
Nvidia and Stanford University Model Human Brain Using GPUs