AI Accelerators
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AI Accelerators
A neural processing unit (NPU), also known as AI accelerator or deep learning processor, is a class of specialized hardware acceleration, hardware accelerator or computer system designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision. Use Their purpose is either to efficiently execute already trained AI models (inference) or to train AI models. Their applications include algorithms for robotics, Internet of things, and data (computing), data-intensive or sensor-driven tasks. They are often Manycore processor, manycore designs and focus on precision (computer science), low-precision arithmetic, novel dataflow architectures, or in-memory computing capability. , a typical AI integrated circuit chip transistor count, contains tens of billions of MOSFETs. AI accelerators are used in mobile devices such as Apple iPhones and Huawei cellphones, and personal computers such as Intel laptops, AMD laptop ...
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Hardware Acceleration
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix of both. To perform computing tasks more efficiently, generally one can invest time and money in improving the software, improving the hardware, or both. There are various approaches with advantages and disadvantages in terms of decreased latency, increased throughput, and reduced energy consumption. Typical advantages of focusing on software may include greater versatility, more rapid development, lower non-recurring engineering costs, heightened portability, and ease of updating features or patching bugs, at the cost of overhead to compute general operations. Advantages of focusing on hardware may include speedup, reduced power c ...
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