LLC, positioned between external memory and internal subsystems, stores frequently accessed data close to compute resources.

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — ...

Accelerating memory-dependent AI processes, Penguin's MemoryAI KV cache server increases memory capacity by integrating 3 TB of DDR5 main memory and up to eight 1 TB CXL Add-in Cards (AICs). Penguin ...

This article outlines the design strategies currently used to address these bottlenecks, ranging from data center systolic ...

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 ...

How lossless data compression can reduce memory and power requirements. How ZeroPoint’s compression technology differs from the competition. One can never have enough memory, and one way to get more ...

AMD is leveraging one of its latest families of EPYC server CPUs, code-named Genoa X, in-house to run the electronic design automation (EDA) tools it uses for product development. Based on TSMC's 5-nm ...

The latest Area-51 desktop from Alienware centers around AMD’s Ryzen 7 9800X3D, an 8-core processor with 104MB of total cache designed for gaming workloads. Paired with an RTX 5080 graphics card, 64GB ...

In the eighties, computer processors became faster and faster, while memory access times stagnated and hindered additional performance increases. Something had to be done to speed up memory access and ...