By processing data in or near memory, there is less resulting data that is transmitted to the AI engines, further reducing the power spent moving data.

By storing AI model weights directly within memory elements and performing matrix multiplication inside the memory itself as input data arrives, PiM significantly reduces data transfer overhead. This ...

A team of computer scientists at the University of Toronto recently discovered that a certain type of hardware attack is ...

Last, CXL-DRAM can substantially reduce system latency and accelerate processing HPC workloads of data centers by providing memory capacity in the Tera-bits (Tb) range.

Future CPU applications, such as AI Language Model programming and image processing for 8K UHD video, will require I/O memory access bandwidth in the range of 10 terabytes/sec.

While processor speeds and memory storage capacities have surged in recent decades, overall computer performance remains constrained by data transfers, where the CPU must retrieve and process data ...

Explore strategies for optimizing AI memory and context usage to improve model interactions. Learn about the role of RAG in boosting AI model ...

The fastest in-memory database offers companies unparalleled benefits when it comes to performance, speed, and data processing efficiency.