High-powered performance - DeepNeuron computes its way to third place

DeepNeuron

After six months of intense work, innovation and problem-solving, the Monash DeepNeuron student team has placed equal third in the 8th APAC HPC-AI Competition.

Competing against 49 university teams from across the region, this year’s challenge asked students to push the boundaries of two demanding open-source workloads:

  • HPC Track: Minimising execution time for NWChem computational chemistry simulations across multi-node CPU clusters
  • AI Track: Maximising inference throughput for the DeepSeek-R1 671B reasoning LLM using the SGLang framework on GPU infrastructure

All of this was carried out on some of the largest academic computing systems in the Asia Pacific region including:

  • Singapore’s National Supercomputing Centre (NSCC)
  • Australia’s National Computational Infrastructure (NCI)
  • Firmus AI Cloud

Meet the team

  • Josh Riantoputra Monash (Team Captain) – Bachelor of Science Advanced (Research) (Hons), 4th year
  • Isaac Barnes – Bachelor of Engineering (Hons), 4th year
  • Luca Lowndes – Bachelor of Engineering (Hons) and Computer Science, 1st year
  • Nathan Culshaw – Bachelor of Computer Science Advanced (Hons), 3rd year
  • Giacomo Bonomi – Advanced Computer Science (Hons), 3rd year

This group operated with minimal supervision on extraordinarily complex tasks, an outstanding result by any measure. This success highlights Monash University’s leadership in High Powered Computing education and AI systems engineering.

The team will receive their award at SupercomputingAsia 2026 in Osaka, and are exploring opportunities for support to attend and continue building on this momentum.

Learn more about Monash DeepNeuron here.

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