Tabular intelligence for the data that runs business.
Joined January 2025
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We are releasing an improved version of metal-graph library, 0.1.2. We've made some substantial changes to the underlying algorithms, which has resulted in significant speedups in our testing. This is still a very early experimental release, and we need to implement a lot more tests, especially under some real-world scenarios, but we feel confident that this already a very strong library that can be used for many projects where graph computations are relevant. Please go check it out. As always, feedback, critique, and any other comments are more than welcome.
Install it simply on your Mac via
python3 -m pip install --upgrade metal-graph==0.1.2
Bojan Tunguz retweeted
We are releasing mlx-geospatial: a Python library for fast geospatial work on Apple silicon, built on MLX. It handles point-in-polygon queries, spatial joins, distances and nearest neighbors. A few results from pre-release benchmarks on an M4 Max:
1/9
After user feedback and further optimization, mlx-geospatial 0.1.1 is out! Faster spatial joins + kNN on Apple silicon.
Warm-index component benchmarks:
M1 Ultra: 18–1,262× (median 95×)
M4 Max: 21–2,005× (median 105×)
CPU/MLX ratios, shown on the same scale.
1/4
The complete-join MLX pipeline beat GeoPandas:
M1 Ultra: 3.78–18.66×
M4 Max: 2.55–16.51×
Six synthetic workloads. Fresh indexes, exact boundaries, all matches, full GeoDataFrames + sorting. Median of 3 paired trials after warmup.
3/4
New: threaded Point extraction, faster polygon-edge searches and boundary refinement, plus chord-distance rejection for kNN.
721 tests per Mac. All 48 full-output checks passed.
pip install -U mlx-geospatial
github.com/tabulai/mlx-geosp…
4/4
We are releasing mlx-geospatial: a Python library for fast geospatial work on Apple silicon, built on MLX. It handles point-in-polygon queries, spatial joins, distances and nearest neighbors. A few results from pre-release benchmarks on an M4 Max:
1/9
Bojan Tunguz retweeted
metal-graph 0.1.1 is out! ⚡
Millions of links. Hub and authority scores in milliseconds.
This update brings HITS graph ranking to Apple Silicon GPUs through native Metal kernels, with Python and C APIs. Here are the M4 Max results. 🧵
1/7
Bojan Tunguz retweeted
metal-graph 0.1.1 is out! Another graph algorithm sped-up on Apple Silicon to a ludicrous degree. Go check it out.
metal-graph 0.1.1 is out! ⚡
Millions of links. Hub and authority scores in milliseconds.
This update brings HITS graph ranking to Apple Silicon GPUs through native Metal kernels, with Python and C APIs. Here are the M4 Max results. 🧵
1/7
HITS ranks authorities and the hubs that link to them—useful for link analysis and knowledge graphs.
hubs, authorities = mg.hits(G)
It joins PageRank, batched personalized PageRank, BFS, neighborhood extraction, and connected components.
6/7
Available now on PyPI:
python -m pip install -U metal-graph
Requires Apple Silicon, macOS 14+, and Python 3.10–3.14.
Code, examples, full benchmarks, and reproducible scripts:
github.com/tabulai/metal-gra…
