The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...
Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory ...
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 ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Advanced Micro Devices is announcing it is shipping its third-generation ...
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 ...
Tesla indicated in August, 2023 they were activating 10,000 Nvidia H100 cluster and over 200 Petabytes of hot cache (NVMe) storage. This memory is used to train the FSD AI on the massive amount of ...
The dynamic interplay between processor speed and memory access times has rendered cache performance a critical determinant of computing efficiency. As modern systems increasingly rely on hierarchical ...
System-on-chip (SoC) architects have a new memory technology, last level cache (LLC), to help overcome the design obstacles of bandwidth, latency and power consumption in megachips for advanced driver ...