Reconfigurable hardware-based acceleration for machine learning and signal processing
H Woehrle, F Kirchner - Formal Modeling and Verification of Cyber …, 2015 - Springer
Formal Modeling and Verification of Cyber-Physical Systems: 1st International …, 2015•Springer
Certain application areas of signal processing and machine learning, such as robotics,
impose technical limitations on the computing hardware, which make the use of generic
processors unfeasible. In this paper we propose a framework for the development of
dataflow accelerators as a possible solution. The approach is based on model based
development and code generation to allow a rapid development of the accelerators and
perform a functional verification of the overall system.
impose technical limitations on the computing hardware, which make the use of generic
processors unfeasible. In this paper we propose a framework for the development of
dataflow accelerators as a possible solution. The approach is based on model based
development and code generation to allow a rapid development of the accelerators and
perform a functional verification of the overall system.
Abstract
Certain application areas of signal processing and machine learning, such as robotics, impose technical limitations on the computing hardware, which make the use of generic processors unfeasible. In this paper we propose a framework for the development of dataflow accelerators as a possible solution. The approach is based on model based development and code generation to allow a rapid development of the accelerators and perform a functional verification of the overall system.
Springer
以上显示的是最相近的搜索结果。 查看全部搜索结果