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 ...
Google AI breakthrough TurboQuant reduces KV cache memory 6x, improving chatbot efficiency, enabling longer context and faster real-time AI inference.
The authors report on the design of efficient cache controller suitable for use in FPGA-based processors. Semiconductor memory which can operate at speeds comparable with the operation of the ...
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Mastering cache design for faster computing
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 ...
Magneto-resistive random access memory (MRAM) is a non-volatile memory technology that relies on the (relative) magnetization state of two ferromagnetic layers to store binary information. Throughout ...
Why it matters: A RAM drive is traditionally conceived as a block of volatile memory "formatted" to be used as a secondary storage disk drive. RAM disks are extremely fast compared to HDDs or even ...
A new technical paper titled “ARCANE: Adaptive RISC-V Cache Architecture for Near-memory Extensions” was published by researchers at Politecnico di Torino and EPFL. Abstract “Modern data-driven ...
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