Most of the energy an AI chip burns never goes toward actual computation. It goes toward moving data: shuttling model weights ...

Google introduces TurboQuant, a compression method that reduces memory usage and increases speed ...

A new hardware-software co-design increases AI energy efficiency and reduces latency, enabling real-time processing of ...

In modern CPU device operation, 80% to 90% of energy consumption and timing delays are caused by the movement of data between the CPU and off-chip memory. To alleviate this performance concern, ...

Memory is no longer just supporting infrastructure; it's now become a primary determinant of system performance, cost and ...

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...

Researchers have developed a new type of optical memory called a programmable photonic latch that is fast and scalable, enabling temporary data storage in optical processing systems and offering a ...