Arm Research Summit 2019
Poster Presentation, , Austin
A Configurable Simulator for Customized Accelerators on SoCs. Poster
Talks and Presentations
2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)
Conference Proceedings Talk, UCSD Campus, San Diego, CA, USA
This paper describes a flexible infrastructure for fast computer architecture simulation and prototyping of accelerator IP. A trend for System-on-Chips is to include application specific accelerators on the die. However, there is still a key research problem that needs to be addressed: How do hardware accelerators interact with the processors of a system and what is the impact on overall performance? To solve this problem, we propose an infrastructure that can directly simulate unmodified application executables with FPGA hardware accelerators. Unmodified application binaries are dynamically instrumented to generate processor load/store and program counter events and any memory accesses generated by accelerators, that are sent to an FPGA-based out-of-order pipeline model. The key features of our infrastructure are the ability to code exclusively at the user level, to dynamically discover and use available hardware models at run time, to test and simultaneously optimize hardware accelerators in an heterogeneous system. In terms of evaluation, we present a comparison between our system and Gem5 to demonstrate accuracy and relative performance, using the SPEC CPU benchmarks; even though our system is implemented on Zynq XC7045 which integrates dual 667MHz Arm Cortex-A9s with substantial FPGA resources, it outperforms Gem5 running on a Xeon E3 3.2 GHz with 32GBs of RAM. We also evaluate our infrastructure in simulating the interaction of accelerators with processors using accelerators taken from the Mach Benchmark Suite and other custom accelerators from computer vision applications.
Arm Research Summit 2018
Poster Presentation, Robinson College, Cambridge, United Kingdom
Fast Micro-Architectural Simulation on FPGAs using Dynamic Binary Modification. Poster