Chinese team develops faster, more efficient data sorting system for AI and computing
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Their new sorting system relies on memristors, an electronic circuit component with memory-like abilities, along with a sorting algorithm to enable more efficient data processing.
The team built a memristor-based hardware sorting prototype to demonstrate tasks such as route finding and neural network inference, achieving both speed and energy efficiency improvements over traditional sorting methods.
'Sorting is a performance bottleneck in numerous applications, including artificial intelligence, databases, web search and scientific computing,' the team said in a paper published in the peer-reviewed journal Nature Electronics on June 25.
Computing systems are typically based on Von Neumann architecture, which separates data storage – or memory – and processing, such as through the use of a central processing unit (CPU).
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This has led to the Von Neumann bottleneck, a limit on the speed of data transfer between the main memory and processing unit.
'Sort-in-memory using memristors could help overcome these limitations, but current systems still rely on comparison operations so that sorting performance remains limited,' said the researchers from Peking University and the Chinese Institute for Brain Research.
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