Harini Muthukrishnan (U of Michigan); David Nellans, Daniel Lustig (NVIDIA); Jeffrey A. Fessler, Thomas Wenisch (U of Michigan). Abstract—”Despite continuing research into inter-GPU communication ...
Understanding GPU memory requirements is essential for AI workloads, as VRAM capacity--not processing power--determines which models you can run, with total memory needs typically exceeding model size ...
Nvidia Corp. today disclosed that it has acquired Run:ai, a startup with software for optimizing the performance of graphics card clusters. The terms of the deal were not disclosed. TechCrunch, citing ...
Crusoe, the industry’s first vertically integrated AI infrastructure provider, is announcing its acquisition of Atero, the company specializing in GPU management and memory optimization for AI ...
GSI Gemini-I APU reduces constant data shuffling between the processor and memory systems Completes retrieval tasks up to 80% faster than comparable CPUs GSI Gemini-II APU will deliver ten times ...
As enterprises seek alternatives to concentrated GPU markets, demonstrations of production-grade performance with diverse ...
Modern compute-heavy projects place demands on infrastructure that standard servers cannot satisfy. Artificial intelligence ...
Belgian research lab Imec has revealed 3D stacked memory-on-GPU AI processor thermal data at IEDM (IEEE International Electron Devices Meeting) this week. The data comes from a thermal STCO ...
The use of Graphics Processing Units (GPUs) to accelerate the Finite Element Method (FEM) has revolutionised computational simulations in engineering and scientific research. Recent advancements focus ...
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