In the intricate world of modern chip architectures, the “memory wall” – the limitations posed by external DRAM accesses on performance and power consumption growing slower than the ability to compute ...
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.
Performance modeling plays an essential role in processor design. It can help in determining the architectural parameters that are crucial for optimal performance. Earlier researchers used simulations ...
Nvidia CEO Jensen Huang recently declared that artificial intelligence (AI) is in its third wave, moving from perception and generation to reasoning. With the rise of agentic AI, now powered by ...
Open-source OCR from Baidu eliminates the GPU memory wall that limits long-document parsing. Unlimited OCR uses a constant KV ...
Memory-centric challenger brings its full silicon-to-rack inference stack to Hamburg, arguing that inference economics turn on memory architecture and capacity: the ability to actually use the ...
The data processing demands of the digital era have exposed limitations in conventional memory architectures. Gain cell-embedded dynamic random-access memory based on oxide semiconductors is emerging ...
This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. AI infrastructure cannot evolve at the speed of model innovation. Processor design cycles ...
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 ...
RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results