This article examines five key hardware strategies for building energy-efficient AI acceleration: dedicated accelerator ...

Enfabrica Corp.’s hybrid memory fabric system designed to improve efficiencies in large-scale distributed, memory-bound AI ...

Enfabrica Corporation, an industry leader in high-performance networking silicon for artificial intelligence (AI) and ...

and restoring that state when the machine is back up and running. Bringing checkpointing capability to big memory architectures with pooled, distributed memory across multiple nodes operating on large ...

Existing distributed computing frameworks are failing to keep a lid on the growing computational, memory and even energy costs resulting from the constantly expanding volume Big Data for anything ...

Computer engineer embarks on bold project for a new vision of distributed shared memory With the support of a new NSF grant, Professor of Computer Science and Engineering Peter Alvaro is embarking on ...

Using Consumer GPUs: Considering the fact that each server possesses at least 16 GB of CPU RAM and 8 GB of GPU memory, the primary objective is to minimize the model's memory footprint, enabling ...