Abstract

As modern FPGAs evolve to include more heterogeneous processing elements, such as ARM cores, it makes sense to consider these devices as processors first and FPGA accelerators second. As such, the conventional FPGA development environment must also adapt to support more software-like programming functionality. While high-level synthesis tools can help reduce FPGA development time, there still remains a large expertise gap in order to realize highly performing implementations. At a system-level the skill set necessary to integrate multiple custom IP hardware cores, interconnects, memory interfaces, and now heterogeneous processing elements is complex. Rather than drive FPGA development from the hardware up, we consider the impact of leveraging Python to accelerate application development. Python offers highly optimized libraries from an incredibly large developer community, yet is limited to …

Date

2017

Authors

Andrew G Schmidt, Gabriel Weisz, Matthew French

Conference

2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)

Pages

121-124

Publisher

IEEE