Abstract: Memory encryption with authentication protects critical applications from attackers with physical access. Memory encryption introduces memory access latency overhead due to the cryptographic ...

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 ...

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 ...

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 ...

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 ...

Many people who were active when they were young end up inadvertently taking a long break from sport in adulthood. Perhaps you lifted weights in your teens and 20s, then had kids and didn't get back ...

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 ...