Abstract: A reconfigurable $\mathbf{1 6 K B}$ cache memory system is designed using Verilog Hardware Description Language to support multiple cache mapping techniques, including direct-mapped and ...

Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

DRAM decides how your drive actually performs under pressure.

At 100 billion lookups/year, a server tied to Elasticache would spend more than 390 days of time in wasted cache time.

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

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, ...

Nabsys and the Research Lab of Dr. Martin Taylor, Brown University, Present Data Using the OhmX™ Platform at AGBT 2026 EGM enables the direct detection of endonuclease activity at the genome scale by ...

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

Memory giants Micron, SK Hynix and Samsung have led a rally in semiconductor stocks this year. Memory prices surged in 2025 and are likely to increase further in 2026 as demand for these chips which ...

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 ...