The researchers’ findings point to significant opportunities for GSI Technology as customers increasingly require performance-per-watt gains across various industries, including Edge AI for ...
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.
"Firstly, traditional sorting hardware involves extensive comparison and select logic, conditional branching, or swap operations, featuring irregular control flow that fundamentally differs from the ...
Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
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 ...
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