Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

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 ...

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 ...

Lightbits Labs Ltd. today is introducing a new architecture aimed at addressing one of the most stubborn bottlenecks in large-scale artificial intelligence inference: the growing mismatch between the ...

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

DRAM access latency is typically 50–100 ns, which at 3 GHz corresponds to 150–300 cycles. Latency arises from signal propagation, memory controller scheduling, row activation, and bus turnaround. Each ...

A new technical paper titled “Leveraging Chiplet-Locality for Efficient Memory Mapping in Multi-Chip Module GPUs” was published by researchers at Electronics and Telecommunications Research Institute ...

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 ...

Generative AI is arguably the most complex application that humankind has ever created, and the math behind it is incredibly complex even if the results are simple enough to understand. GenAI also it ...