Simple-V Vectorisation has some extremely unusual data manipulation properties that negate the need for such heavy optimisation. We would like to explore this in-depth, for example examining Galois Field arithmetic, the basis of Elliptic Curve, AES, Error-correction algorithms and more, at the fundamental mathematical level and providing Vector Matrix Multiply and other abstractions, the combination of which lead to auditors to be able to see extremely clearly and quickly what the relationship is between the math and the actual implementation in hardware. The focus will be on investigation and implementation of cryptographic primitives for use in Blockchain, OpenSSL, on keeping the implementation simple and leveraging Formal Correctness Proofs to verify them.
-The target worked example will be not to simply put this into an FPGA but to put together a 130nm ASIC under the Google Skywater Open PDK ASIC Programme, as a proof-of-concept Gigabit Router chip capable of securely handling network traffic and, having the underlying cryptographic primitives in place, being the basis of peer networking and blockchain applications which can be trusted with thode tasks by its full HDL and source code being publicly available for independent review.
+The target worked example will be not to simply put this into an FPGA but to put together a 130nm ASIC under the Google Skywater Open PDK ASIC Programme, as a proof-of-concept Gigabit Router chip capable of securely handling network traffic and, having the underlying cryptographic primitives in place, being the basis of peer networking and blockchain applications which can be trusted with those tasks by its full HDL and source code being publicly available for independent review.
Ultimately we want a demonstration ASIC of an independently-auditable hardware implementation which can be trusted by end-users.
projects / libreriscv.git / commitdiff