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 ...

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 ...

The cost associated with moving data in and out of memory is becoming prohibitive, both in terms of performance and power, and it is being made worse by the data locality in algorithms, which limits ...

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 ...