“Many modern workloads such as neural network inference and graph processing are fundamentally memory-bound. For such workloads, data movement between memory and CPU cores imposes a significant ...

The portion of a computer’s RAM that is used by a hardware device such as a GPU (Graphics Processing Unit), sound card, network adapter, and other hardware components is known as Hardware Reserved.

Artificial intelligence has been bottlenecked less by raw compute than by how quickly models can move data in and out of memory. A new generation of memory-centric designs is starting to change that, ...

Lawrence Livermore National Laboratory has long been one of the world’s largest consumers of supercomputing capacity. With computing power of more than 200 petaflops, or 200 billion floating-point ...

Like AWS, Google’s custom silicon efforts continued to soar in 2025 with the announcement of its seventh-generation Tensor ...

“Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with ...

Chrome uses a hardware acceleration technology called the Graphics processing unit (GPU) to handle visual and graphic processing, and it also helps to show the web page correctly. When some users ...

Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, ...

The Spectre and Meltdown vulnerabilities in 2018 exposed computer memory as an easy target for hackers to inject malicious code and steal data. The aftermath spurred the adoption of memory-safe chips ...