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 ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...

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 ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

Cache memory significantly reduces time and power consumption for memory access in systems-on-chip. Technologies like AMBA protocols facilitate cache coherence and efficient data management across CPU ...

Many people have heard the term cache coherency without fully understanding the considerations in the context of system-on-chip (SoC) devices, especially those using a network-on-chip (NoC). To ...