The 2021 A. M. Turing Award celebrates Jack Dongarra’s contributions in high-performance computing, which have had a significant impact in computational science.

Dr Jack Dongarra, Distinguished Professor at the University of Tennessee and recipient of the 2021 A. M. Turing Award, spoke with Nature Computational Science about his contributions to high-performance computing (HPC) and his insights into the future of this field.

The yin–yang codec transcoding algorithm is proposed to improve the practicality and robustness of DNA data storage.

Smart pandemic mitigation strategies are proposed to strategically close higher-risk economic sectors, while allowing dozens of other economic sectors to continue. This would enable schools to remain open and keep hospitalizations within capacity.

Weight-sharing is used to accelerate and to effectively pretrain neural network-based variational Monte Carlo methods when solving the electronic Schrödinger equation for multiple geometries.

Associating biotechnology to its lab of origin is a challenging task. A deep learning approach is proposed to find distances between engineered plasmids, which allows the ranking of their most probable labs of origin with high accuracy.

A protocol is developed to construct multi-domain protein structures from cryo-electron microscopy density maps. The results demonstrate the effectiveness of deep-learning-guided inter-domain structure assembly and refinement simulations.

Smart pandemic mitigation strategies are proposed to strategically close higher-risk economic sectors, while allowing dozens of other economic sectors to continue. This would enable schools to remain open and keep hospitalizations within capacity.

Unified structural descriptors of geometrical and graph-theoretical features are developed, allowing knowledge about protein lock-and-key complexes to be utilized to predict the formation of and interaction sites in protein–nanoparticle pairs.

The yin–yang codec transcoding algorithm is proposed to improve the practicality and robustness of DNA data storage.

Normative modeling is considered one of the most promising avenues towards personalized medicine. The integration of multimodal, mechanistic and lifespan modeling will play an essential role, but significant challenges need to be overcome before this promise can be turned into reality.

Dr Srijan Kumar, assistant professor at Georgia Institute of Technology and a Forbes 30 Under 30 honoree in science, discusses with Nature Computational Science how he uses machine learning and data science to identify and mitigate malicious activities on online platforms, including misinformation and anti-Asian hate speech.