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 ...

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 ...

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 ...

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 ...

A new technical paper titled “MLP-Offload: Multi-Level, Multi-Path Offloading for LLM Pre-training to Break the GPU Memory Wall” was published by researchers at Argonne National Laboratory and ...

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 ...

3D HBM-on-GPU design reaches record compute density for demanding AI workloads Peak GPU temperatures exceeded 140°C without thermal mitigation strategies Halving the GPU clock rate reduced ...

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.