Ng, Ivan Yong Zhe (2026) RISC-V instruction set extension for blockchain token transaction. Final Year Project, UTAR.
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Abstract
This project investigates the implementation of RISC-V Instruction Set Architecture (ISA) extensions within SP1 zkVM to accelerate blockchain token transaction workloads. SP1 zkVM executes programs compiled to the RISC-V RV32IM instruction set and generates zero-knowledge proofs of their correct execution. However, software-implemented cryptographic operations such as SHA-256, Keccak-256, and Ed25519 generate long instruction traces inside the virtual machine, directly increasing the cost of proof generation. This project designs and implements three ISA extensions — SHA256_FOLD, SPONGE_F1600, and TED255_ADD — within SP1's dedicated 0x01_xx_xx_xx syscall namespace, wiring each extension through all four layers of SP1's syscall architecture without modifying the underlying proof constraint system. A benchmark suite is developed to evaluate instruction count, instruction speedup, transactions per second, and execution speedup across 1, 10, and 100 iteration scales for SHA-256, Keccak-256, Ed25519, and a composite token transaction workload. Results show instruction speedup of 6.0 times for SHA-256, 21.0 times for Keccak-256, and 559.6 times for Ed25519 at 100 iterations. The composite token transaction benchmark achieves 64.6 times instruction speedup and 3,030 transactions per second compared to 157.7 for the baseline. These results demonstrate that direct precompile syscall invocation substantially reduces instruction trace length for blockchain token transaction workloads in SP1 zkVM.
| Item Type: | Final Year Project / Dissertation / Thesis (Final Year Project) |
|---|---|
| Subjects: | T Technology > T Technology (General) T Technology > TD Environmental technology. Sanitary engineering |
| Divisions: | Faculty of Information and Communication Technology > Bachelor of Computer Science (Honours) |
| Depositing User: | ML Main Library |
| Date Deposited: | 05 Aug 2026 18:51 |
| Last Modified: | 05 Aug 2026 18:51 |
| URI: | http://eprints.utar.edu.my/id/eprint/7757 |
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