An Extended GASNet API for PGAS Programming on a Zynq SoC Cluster
Sanket N. Pandit · TSpace (University of Toronto) · 2016
This work presents a dynamic development flow to integrate FPGA accelerators into software applications for a Zynq SoC cluster. We provide a high-level library, THe\_GASNet Extended API, based on the Partitioned Global Address Space (PGAS) programming model for remote memory operations. The extended API is built using the THe\_GASNet Core API that implements a global address space view of the memory but provides distinction between local and remote data accesses. The extended API provides an expressive way to implement parallel applications on the x86-ARM-FPGA heterogeneous systems. For the benchmark, we implemented the Jacobi iterative method on the cluster. The hardware implementation of the Jacobi method performs 2.78-fold faster than the software implementation on the i5 processor for a 4096x4096 surface. Compared to the core API, the extended API performs slightly worse for all the data sizes. However, the trade-off of the reduced performance is increased ease of programming.