The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...

Memory-augmented Large Language Models (LLMs) have demonstrated remarkable capability for complex and long-horizon embodied planning. By keeping track of past experiences and environmental states, ...

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 ...

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 ...

Paper: Agent Memory Below the Prompt: Persistent Q4 KV Cache for Multi-Agent LLM Inference on Edge Devices (PDF) When multiple LLM agents share one local model, every new request re-computes the full ...

In an effort to work faster, our devices store data from things we access often so they don’t have to work as hard to load that information. This data is stored in the cache. Instead of loading every ...

AMD recently published a new patent that reveals that the company is working on making its 3D V-cache tech even better. Back in early 2021, we started hearing the first whispers and murmurs of a new ...

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 ...

this error appears in the terminal: Error: Could not load REST Cache provider "memory". You may need to install a provider plugin "yarn add @strapi-community/provider ...