Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

LLC, positioned between external memory and internal subsystems, stores frequently accessed data close to compute resources.

MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — ...

Cache, in its crude definition, is a faster memory which stores copies of data from frequently used main memory locations. Nowadays, multiprocessor systems are supporting shared memories in hardware, ...

Lightbits Labs Ltd. today is introducing a new architecture aimed at addressing one of the most stubborn bottlenecks in large-scale artificial intelligence inference: the growing mismatch between the ...

The year so far has been filled with news of Spectre and Meltdown. These exploits take advantage of features like speculative execution, and memory access timing. What they have in common is the fact ...

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 ...

In the early days of computing, everything ran quite a bit slower than what we see today. This was not only because the computers' central processing units – CPUs – were slow, but also because ...

In the eighties, computer processors became faster and faster, while memory access times stagnated and hindered additional performance increases. Something had to be done to speed up memory access and ...