google-deepmind/alphatensor resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2853 stars · 257 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Code and data accompanying DeepMind's AlphaTensor publication on discovering faster matrix multiplication algorithms with reinforcement learning. It includes discovered algorithms as tensor factorizations, GPU benchmarking scripts, nonequivalence verification data, and recombination code.

Use cases

• explore discovered matrix multiplication algorithms
• benchmark matrix multiplication speed on NVIDIA GPUs
• verify nonequivalence of matrix multiplication factorizations
• decompose larger matrix multiplication tensors from smaller factorizations
• study reinforcement learning for algorithm discovery

When to choose

• you want to inspect or use AlphaTensor's discovered matrix multiplication algorithms
• you need to benchmark matrix multiplication algorithms on a V100 GPU
• you are reproducing or extending the AlphaTensor research

When to avoid

• you need a production matrix multiplication library for your application
• you want the full AlphaTensor training pipeline, which is not included
• you need a maintained general-purpose linear algebra tool

Facets

dataset · maturity maintenance

machine-learning reinforcement-learning benchmarking math machine-learning python matrix-multiplication alphazero research-code tensor-decomposition deepmind scientific-publication algorithms research linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-deepmind/alphatensor")