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 ...

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 ...

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 ...

[OPINION/INSIGHT ARTICLE] The surging demand for supercomputing power, driven by the insatiable appetite of AI/ML, big data analytics, and scientific research, has driven the HPC industry to push the ...

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 ...

Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.

Deciding on the correct type of GPU accelerated computation hardware depends on many factors. One particularly important aspect is the data flow patterns across the PCIe bus and between GPUs and ...