VANAGA is an open source framework written in Python for the automatic optimization of instruction set encoding of processor architectures. A single-objective or multi-objective genetic algorithm (GA) is used for this purpose. The optimization metrics (e.g. silicon area of the instruction decoder, power dissipation of the processor logic) are customizable by the user. Results are generated by a user external processor design toolflow. Extensively customizable and parallelized interfaces for high evaluation throughput are available for this purpose.
M. Weißbrich, J. A. Moreno-Medina, and G. Payá-Vayá. "Using Genetic Algorithms to Optimize the Instruction-Set Encoding on Processor Cores". 2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2021, https://doi.org/10.1109/mocast52088.2021.9493406
PATARA is an open-source tool for post-silicon validation of any fabricated processor. It is based on the REVERSI methodology in which the processor validates itself. The validation process is performed on random data and random instructions. Therefore this tool can functionally verify functional units, and interactions between functional units and modules.
F. Stuckmann,P. A. Fistanto and G. Payá-Vayá. "PATARA: A REVERSI-Based Open-Source Tool for Post-Silicon Validation of Processor Cores". 2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2021, https://doi.org/10.1109/mocast52088.2021.9493373
