The emergence of approximate computing has opened up a new world of possibilities for hardware designers. Approximate accelerator architectures are becoming increasingly popular for their ability to provide high performance and energy efficiency. Field Programmable Gate Arrays (FPGAs) are a type of reconfigurable hardware that can be used to implement these approximate accelerators. Automated frameworks are now available to help designers explore the potential of FPGA-based approximate accelerators.
Approximate accelerators are designed to trade off accuracy for performance and energy efficiency. This is done by introducing errors into the computation process, which can be tolerated in many applications. By using approximate accelerators, designers can achieve significant performance improvements and energy savings compared to traditional exact accelerators.
FPGAs are an ideal platform for implementing approximate accelerators due to their reconfigurability and flexibility. They can be programmed to implement custom hardware designs that can be tailored to specific applications. Automated frameworks are now available to help designers explore the potential of FPGA-based approximate accelerators. These frameworks provide a high-level programming interface that allows designers to quickly and easily create and evaluate approximate accelerators on FPGAs.
These automated frameworks provide a number of advantages over traditional design approaches. They enable designers to quickly explore a range of different accelerator architectures, allowing them to quickly identify the best design for their application. They also allow designers to evaluate the performance and energy efficiency of their designs in a fraction of the time required by traditional approaches.
In summary, automated frameworks are now available to help designers explore the potential of FPGA-based approximate accelerators. These frameworks provide a high-level programming interface that allows designers to quickly and easily create and evaluate approximate accelerators on FPGAs. They enable designers to quickly explore a range of different accelerator architectures, allowing them to quickly identify the best design for their application. They also allow designers to evaluate the performance and energy efficiency of their designs in a fraction of the time required by traditional approaches.
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