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.

The artificial intelligence buildout is quietly rewriting the semiconductor pecking order, shifting pricing power from headline-grabbing compute chips to the memory and storage that feed them. As ...

Content Addressable Memory (CAM) is an advanced memory architecture that performs parallel search operations by comparing input data against all stored entries simultaneously, rather than accessing ...

TL;DR: The NVIDIA GeForce RTX 5080 is expected to feature 16GB GDDR7 memory, offering up to 960GB/sec bandwidth and 400W power consumption. It promises significant performance improvements, especially ...