Agile SoC Development with Open ESP

ESP is an open-source research platform for heterogeneous SoC design. The platform combines a modular tile-based architecture with a variety of application-oriented flows for the design and optimization of accelerators. The ESP architecture is highly scalable and strikes a balance between regularity and specialization. The companion methodology raises the level of abstraction to system-level design and enables an automated flow from software and hardware development to full-system prototyping on FPGA. For application developers, ESP offers domain-specific automated solutions to synthesize new accelerators for their software and to map complex workloads onto the SoC architecture. For hardware engineers, ESP offers automated solutions to integrate their accelerator designs into the complete SoC. Conceived as a heterogeneous integration platform and tested through years of teaching at Columbia University, ESP supports the open-source hardware community by providing a flexible platform for agile SoC development.Comment: Invited Paper at the 2020 International Conference On Computer Aided Design (ICCAD) - Special Session on Opensource Tools and Platforms for Agile Development of Specialized Architecture

Comparison of Cache Replacement Algorithms for RISC-V

Cache replacement policies play a significant role in the performance of cache memories. This thesis aims to find new replacement algorithm options for an existing RISC-V multicore processor design, the HPC subsystem of the Ballast System-on-Chip. HPC is a dual core design with two 64-bit CVA6 cores, and it features an L2 cache. The cache was originally designed with a simple but popular LRU replacement algorithm. This work first looks at the cache replacement algorithms used by other existing RISC-V systems, and then at other research that has been carried out on the topic. Three algorithms are implemented as part of the HPC L2 cache: PLRUm, EBR, and Mockingjay. The performance of these algorithms is evaluated in RTL simulation with a set of benchmark programs. The results show that more complex EBR and Mockingjay algorithms have a concrete performance improvement over LRU-based solutions in most cases, but the LRU algorithms do have an edge on a few benchmarks. The performance improvement provided by more advanced algorithm comes at a cost, as they require more memory and registers