Ashwin Kumar Karnad
The deRSE25 conference marked my first experience in a gathering centered around research software engineering and technical conferences in general. Meetings like this give you exposure to a wide variety of topics, succinctly.
For example, I was introduced to the FAIR (Findable, Accessible, Interoperable, Reproducible) principles and discovered various tools developed around this concept. I also participated in RSQKit, an initiative to help develop such resources myself.
Outside of the workshops, authors enthusiastically shared their research software experiences and explorations in talks. These covered diverse topics, from new hardware design languages and privacy-preserving computing, to ML for dance education, and challenges in recording high-resolution free-moving animals or even integrating multiple sensors in a cloud chamber. Although some challenges they mentioned were specific to their fields, they provided valuable insights.
I resonated with many participants, sharing aspirations like pursuing a PhD part-time. The snack breaks were the perfect time to listen to research data horror stories. Turns out a lot of people get into building better research software after experiencing their horror stories! Luckily I have started to pick up on these ideas before mine :).
I even managed to connect with other quantum software engineers like myself, which gave me insights into the state of the art in my field of work. For instance the ideas of integrating formal verification techniques to quantum systems or experiences from other teams and challenges in quantum computing integration.
Presenting a talk on reproducible simulations, inspired by how blockchain performs deterministic computation, was a highlight for me. I am grateful to all my colleagues who contributed to the success of my presentation. Overall, the deRSE25 conference left me wanting more, as the two and a half days flew by in a breeze!
Accepted Abstract for a Talk
Title: Reproducible scientific simulations on the blockchain
Abstract: The reproducibility of scientific simulations is one of the key challenges of scientific research.Current best practices involve version-controlled code, tracking dependencies, specifying hardware configurations, and sometimes using Docker containers to enable one-click simulation setups. However, these approaches still fall short of achieving true reproducibility. For example, Docker depends on the underlying host kernel, and high-performance computing (HPC) codes often link with specific kernel modules and headers. Over time, changes in host kernel versions can render Dockerized simulations unusable. Furthermore, non-deterministic simulations, such as Monte Carlo methods, may not yield identical results even when rerun on the same hardware with the same code.
This talk explores the potential of blockchain technology to address these challenges. By running simulations natively on-chain (via smart contracts) and emitting logs of each state transition, we can achieve reproducibility while also verifying the simulation's authenticity (associating the original author of the simulation and the reporting author).
Other potential ideas include using zero-knowledge proofs to hash the call stack and the stack memory into a Merkle tree or also to think about the tokenisation of compute.
We will delve into the technical feasibility and potential benefits of this approach, including its implications for trust, transparency, and the future of scientific research.