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Скачать или смотреть High Performance Accurate and Approximate Multipliers for FPGA based Hardware Accelerators

  • Nxfee Innovation
  • 2022-10-17
  • 1366
High Performance Accurate and Approximate Multipliers for FPGA based Hardware Accelerators
VLSI IEEE Transactions ONLINE SHOPwww.nxfee.com
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Описание к видео High Performance Accurate and Approximate Multipliers for FPGA based Hardware Accelerators

High Performance Accurate and Approximate Multipliers for FPGA based Hardware Accelerators | Multiplication is one of the widely used arithmetic operations in a variety of applications, such as image/video processing and machine learning. FPGA vendors provide high performance multipliers in the form of DSP blocks. These multipliers are not only limited in number and have fixed locations on FPGAs but can also create additional routing delays and may prove inefficient for smaller bit-width multiplications. Therefore, FPGA vendors additionally provide optimized soft IP cores for multiplication. However, in this work, we advocate that these soft multiplier IP cores for FPGAs still need better designs to provide high-performance and resource efficiency. Towards this, we present generic area-optimized, low-latency accurate and approximate soft-core multiplier architectures, which exploit the underlying architectural features of FPGAs, i.e., look-up table (LUT) structures and fast carry chains to reduce the overall critical path delay and resource utilization of multipliers. Compared to Xilinx multiplier LogiCORE IP, our proposed unsigned and signed accurate architecture provides up to 25% and 53% reduction in LUT utilization, respectively, for different sizes of multipliers. Moreover, with our unsigned approximate multiplier architectures, a reduction of up to 51% in the critical path delay can be achieved with an insignificant loss in output accuracy when compared with the LogiCORE IP. For illustration, we have deployed the proposed multiplier architecture in accelerators used in image and video applications, and evaluated them for area and performance gains.

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