A paper from Google could make local LLMs even easier to run.

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in ...

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

Write-through: all cache memory writes are written to main memory, even if the data is retained in the cache, such as in the example in Figure 4.11. A cache line can be in two states – valid or ...

When talking about CPU specifications, in addition to clock speed and number of cores/threads, ' CPU cache memory ' is sometimes mentioned. Developer Gabriel G. Cunha explains what this CPU cache ...

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 ...