A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
The biggest challenge posed by AI training is in moving the massive datasets between the memory and processor.
[CONTRIBUTED THOUGHT PIECE] Generative AI is unlocking incredible business opportunities for efficiency, but we still face a formidable challenge undermining widespread adoption: the exorbitant cost ...
Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
"Firstly, traditional sorting hardware involves extensive comparison and select logic, conditional branching, or swap operations, featuring irregular control flow that fundamentally differs from the ...
The children’s fairy tale of ‘Goldilocks and the Three Bears’ describes the adventures of Goldi as she tries to choose among three choices for bedding, chairs, and bowls of porridge. One meal is “too ...
SUNNYVALE, Calif.--(BUSINESS WIRE)--ANAFLASH, a Silicon Valley-based pioneer in low power edge computing, has acquired Legato Logic’s time-based compute-in-memory technologies and its industry ...
The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...
The era of Big Data and Big Compute is here. Per OpenAI, compute demand by deep learning has been doubling every three months for the last 8 years. Neuromorphic computing with deep neural networks is ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback