AccML @ HiPEAC 2026

8th Workshop on Accelerated Machine Learning (AccML)
Co-located with HiPEAC 2026
January 27, 2026
Kraków, Poland

https://accml.dcs.gla.ac.uk/
https://www.hipeac.net/2026/krakow/#/program/sessions/8255/

Recent advances in diverse AI applications have driven the rise of heterogeneous architectures to accelerate machine learning workloads. Increasing model complexity and deployment demands have spurred the development of high-productivity systems, advanced programming abstractions, specialized runtimes, and tools. Since deep learning models are memory- and compute-intensive, acceleration reduces energy use and enables edge deployment. Beyond CNNs, newer models like Vision Transformers and LLMs introduce broader computational challenges, continually testing hardware, software stacks, and abstractions—highlighting the need for dedicated forums on ML acceleration and system design.

Topics of interest:

– Novel ML/AI systems: heterogeneous multi/many-core systems, GPUs, ASICs and FPGAs;
– Software ML/AI acceleration: languages, primitives, libraries, compilers and frameworks;
– Novel ML/AI hardware accelerators and associated software;
– Emerging semiconductor technologies with applications to ML/AI hardware acceleration;
– ML/AI for the design and tuning of hardware, compilers, and systems;
– Cloud and edge ML/AI computing: hardware and software to accelerate training and inference;
– Hardware-Software co-design techniques for more efficient model training and inference (e.g. addressing sparsity, pruning, etc);
– Training and deployment of huge LLMs (such as GPT, Llama), or large GNNs;
– Computing systems research addressing the privacy and security of ML/AI-dominated systems;

Submission
Papers will be reviewed by the workshop’s technical program committee according to criteria regarding the submission’s quality, relevance to the workshop’s topics, and, foremost, its potential to spark discussions about directions, insights, and solutions in the context of accelerating machine learning. Research papers, case studies, and position papers are all welcome.
In particular, we encourage authors to submit work-in-progress papers: To facilitate sharing of thought-provoking ideas and high-potential though preliminary research, authors are welcome to make submissions describing early-stage, in-progress, and/or exploratory work in order to elicit feedback, discover collaboration opportunities, and spark productive discussions.

The workshop does not have formal proceedings.

Important Dates
Submission deadline: November 21, 2025
Notification of decision: December 5, 2025

Organizers
José Cano (University of Glasgow)
Valentin Radu (University of Sheffield)
José L. Abellán (University of Murcia)
Marco Corner (Google DeepMind)
Ulysse Beaugnon (Google DeepMind)
Juliana Franco (Google DeepMind)