AI accelerator

An AI accelerator is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and machine vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability. , a typical AI integrated circuit chip contains billions of MOSFET transistors. A number of vendor-specific terms exist for devices in this category, and it is an emerging technology without a dominant design. Computer systems have frequently complemented the CPU with special-purpose accelerators for specialized tasks, known as coprocessors. Notable application-specific hardware units include video cards for graphics, sound cards, graphics processing units and digital signal processors. As deep learning and artificial intelligence workloads rose in prominence in the 2010s, specialized hardware units were developed or adapted from existing products to accelerate these tasks. Benchmarks such as MLPerf may be used to evaluate the performance of AI accelerators. First attempts like Intel's ETANN 80170NX incorporated analog circuits to compute neural functions. Later all-digital chips like the Nestor/Intel Ni1000 followed. As early as 1993, digital signal processors were used as neural network accelerators to accelerate optical character recognition software. Already in 1988, Wei Zhang et al. discussed fast optical implementations of convolutional neural networks for alphabet recognition. In the 1990s, there were also attempts to create parallel high-throughput systems for workstations aimed at various applications, including neural network simulations. FPGA-based accelerators were also first explored in the 1990s for both inference and training. Smartphones began incorporating AI accelerators starting with the Qualcomm Snapdragon 820 in 2015.