Accelerating memory-dependent AI processes, Penguin's MemoryAI KV cache server increases memory capacity by integrating 3 TB ...

MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — without the hours of GPU training that prior methods required.

For the past few years, AI infrastructure has focused on compute above all other metrics. More accelerators, larger clusters and higher FLOPS drove the conversation to make the most of GPUs. This ...

System-on-a-Chip (SoC) designers have a problem, a big problem in fact, Random Access Memory (RAM) is slow, too slow, it just can’t keep up. So they came up with a workaround and it is called cache ...

The advent of cloud computing, deep learning, and AI could revolutionize modern computing, but they've also created scaling problems. The vast majority of databases use a similar architecture: DRAM ...