Abstract: Cache memory has been introduced to accelerate embedded system performance and is automatically managed without programmer intervention through hardware-based cache controllers. However, ...

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...

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, ...

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 ...

As AI workloads extend across nearly every technology sector, systems must move more data, use memory more efficiently, and respond more predictably than traditional design methodologies allow. These ...

If you’ve looked to upgrade your laptop, add memory to your PC, or even want to pick up a new games console in recent months, you’ll no doubt have noticed prices are higher than ever. RAMageddon is ...

Shimon Ben-David, CTO, WEKA and Matt Marshall, Founder & CEO, VentureBeat As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into ...

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 ...

PrimoCache delivers noticeable speed improvements on systems with ample RAM and slower drives that frequently read and write data, while on high-end systems its main benefit is reducing wear and tear ...