As large language models scale to longer context windows and serve more concurrent users, the key-value (KV) cache has emerged as a primary memory bottleneck in production inference systems. For a ...

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 ...

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 ...

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

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 ...

A new technical paper titled “ARCANE: Adaptive RISC-V Cache Architecture for Near-memory Extensions” was published by researchers at Politecnico di Torino and EPFL. Abstract “Modern data-driven ...

It’s easy to look strictly at the type of CPU and GPU you have when evaluating the kind of performance you’re likely to get in PC games. But beyond that lies another important stat, the CPU cache.