BEIJING, April 21 (Xinhua) -- Intel Corporation of the United States has released a large-scale neuromorphic system called Hala Point, which aims to support cutting-edge research in the field of brain-inspired artificial intelligence and solve the challenges of artificial intelligence in terms of efficiency and sustainability.
Based on its first-generation large-scale research system, Pohoiki Springs, Intel has improved the architecture of the Hala Point Large Neuromorphic System, increasing neuronal capacity by more than 10x and performance by 12x, according to a press release issued by Intel Corporation. Originally deployed at Sandia National Laboratories in the United States, the Hala Point system consists of 1,152 Intel Loihi 2 processors, including 1.15 billion artificial neurons and 128 billion artificial synapses distributed across 140544 processing cores. When running a traditional deep neural network, 20 quadrillions per second can be performed.
The Hala Point system is based on neuromorphic computing technology, which improves the performance and efficiency of mainstream, conventional deep learning models, especially those used to handle real-time workloads such as video, voice and wireless communications, according to the communiqué. Compared to traditional computers that use a central processing unit and graphics processor, the Hala Point system can perform AI reasoning and process optimization problems up to 50 times faster and consume only one percent of the energy of traditional computers.
Mike Davis, director of the Neuromorphic Computing Lab at Intel Labs, said that the cost of computing power for AI models continues to rise, and the industry needs new computing methods that can be scaled. The Hala Point system combines efficient deep learning with brain-like continuous learning and optimization capabilities, hoping to improve the efficiency and adaptability of large-scale artificial intelligence technology.
Source | Xinhua
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