Yi Li bio photo

Yi Li

Associate Professor

College of Computing and Data Science (CCDS)
Nanyang Technological University (NTU)

Address: Block N4-02b-63
50 Nanyang Avenue, Singapore 639798
Phone: +65 6790 4287

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Our paper [1] in collaboration with Xiaodong Qi and Jiao Jiao was accepted at ICDCS. A quick summary of the paper is given below.

As various optimizations being proposed recently, the performance of blockchains is no longer limited by the consensus protocols, successfully scaling to thousands of transactions per second. To further improve blockchains’ throughput, exploiting the parallelism in smart contract executions becomes a clear solution to resolve the new performance bottleneck. The existing techniques perform concurrency control on smart contract transactions based on pre-determined read/write sets, which can hardly be calculated precisely. As a result, many parallelization opportunities are missed in order to maintain the correctness of transaction executions. In this paper, we propose a novel execution scheduling framework, DMVCC, to further increase the parallelism in smart contract executions, via more fine-grained control on state accesses. DMVCC improves over existing techniques with two key features: (1) write versioning, eliminating the write-write conflicts between transactions, and (2) early-write visibility, enabling other transactions to read the writes from a transaction earlier, before it being committed. We integrated DMVCC into the Ethereum Virtual Machine, to evaluate its performance in real-world blockchain environments. The experimental results show that DMVCC doubles the parallel speedup achievable to a 20× overall speedup, compared with the serial execution baseline, approaching the theoretical optimum.

This year, 83 out of 439 submissions were accepted at ICDCS, which gives an acceptance rate of 18.9%.

References

  1. Qi, X., Jiao, J., & Li, Y. (2023, July). Smart Contract Parallel Execution with Fine-Grained State Accesses. Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems (ICDCS).