The world's first! Significant breakthroughs have been made in China's chip industry

Science and Technology Daily reporter Hua LingRecently, Professor Wu Huaqiang and Associate Professor Gao Bin from the School of Integrated Circuits at Tsinghua University developed the world's first fully integrated memristor memory computing integrated chip that supports efficient on-chip learning (machine learning can be directly completed on the hardware side) based on the memory computing integrated computing paradigm. They have made significant breakthroughs in the field of memristor memory computing integrated chips that support on-chip learning, and are expected to promote artificial intelligence Development in fields such as autonomous driving wearable devices

Science and Technology Daily reporter Hua Ling

Recently, Professor Wu Huaqiang and Associate Professor Gao Bin from the School of Integrated Circuits at Tsinghua University developed the world's first fully integrated memristor memory computing integrated chip that supports efficient on-chip learning (machine learning can be directly completed on the hardware side) based on the memory computing integrated computing paradigm. They have made significant breakthroughs in the field of memristor memory computing integrated chips that support on-chip learning, and are expected to promote artificial intelligence Development in fields such as autonomous driving wearable devices. The relevant results are published online in the latest issue of Science.

Memory resistor memory and computing integrated chip and testing system. Courtesy of Tsinghua University

This chip contains all necessary circuit modules to support complete on-chip learning, successfully completing various on-chip incremental learning function validations such as image classification, speech recognition, and control tasks, demonstrating high adaptability, high energy efficiency, high usability, and high accuracy, effectively strengthening the learning adaptability of intelligent devices in practical application scenarios. Under the same task, the energy consumption of on-chip learning achieved by this chip is only 3% of that of specialized integrated circuit (ASIC) systems under advanced technology, demonstrating excellent energy efficiency advantages and great application potential to meet the high computing power requirements of the artificial intelligence era. This provides an innovative development path for breaking through the energy efficiency bottleneck under von Neumann's traditional computing architecture.

Source: Science and Technology Daily

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