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 ...
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 ...
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 ...
A new technical paper titled “Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System” was published by researchers at Rensselaer Polytechnic Institute and IBM. “Large ...
The memory wall is no longer a theoretical concern. It’s the defining bottleneck in today’s AI, automotive, and data center system-on-chips (SoCs). CPUs operate at GHz frequencies with single-digit ...
Earlier this year, SDxCentral explored the market push behind AI inference – the process where a trained machine learning model generates predictions and outputs from new input data. Dell’Oro Group ...
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 ...
Memory is one of a very few elite electronic components essential to any electronic system. Modern electronics perform extraordinarily complex duties that would be impossible without memory. Your ...
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