TurboQuant breakthrough: Google's TurboQuant compresses LLM KV-cache up to 6x without quality loss, freeing GPU memory and boosting inference speed. Hybrid attention savings: DeltaNet-style ...

A technical paper titled “HMComp: Extending Near-Memory Capacity using Compression in Hybrid Memory” was published by researchers at Chalmers University of Technology and ZeroPoint Technologies.

Google AI breakthrough TurboQuant reduces KV cache memory 6x, improving chatbot efficiency, enabling longer context and faster real-time AI inference.

Cache memory sits at the heart of modern computing performance, bridging the speed gap between processors and main memory. By leveraging principles like temporal and spatial locality, engineers design ...

How lossless data compression can reduce memory and power requirements. How ZeroPoint’s compression technology differs from the competition. One can never have enough memory, and one way to get more ...

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 ...

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 ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

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 ...