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Top 4 Jinja Cluster Projects
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Project mention: Can Intel finally beat ARM on performance per Watt? | news.ycombinator.com | 2026-08-08
Nice and organised work!
My only reservation wrt the core of it is that it tests the cpus on a matrix operations task, and power efficiency in this case refers specifically to doing matrix operations. This is fine if that's the kind of task one wants to optimise for, but it does not necessarily translate to general energy efficiency for a broader spectrum of tasks that most people may do most of the time.
And thus, if one wants to optimise for matrix operations, wouldn't it make sense to use apple's accelerate framework instead of blis/openblas (I think you used blis?)? I compiled hpl to use accelerate [0] on my m1 max (macbook), and ran it with settings almost identical to the original m1 max settings [1]. I get 422 Gflops vs 264 Gflops in m1 max mac studio (docker) [2]. My average draw (using a wall power meter, but not interfaced with computer to keep a log, just me looking at it) is around 55-57W (probably less because it peaked at 57W but the last half was getting around 52W). With the most conservative estimate of 57W, this gave a 7.4 Gflops/W which is second place, just below the m4 mac mini in the benchmark table. The m1 max in the original did 4 Gflops/W (at 66W).
So tbh I do not really trust the conclusion of the benchmark page, except if I miss sth. It is quite nice, organised work anyhow.
[0] https://github.com/tycho/hpl/blob/master/setup/Make.MacOSX_A...
[1] I just fixed the p:q ratio, which was prob not really meant to be 1:10 there, I assume, also judging from the settings in the other tests. I put p=2,q=4. Also I was unable to put more than 8 processes in total.
[2] The original m1 max benchmark: https://github.com/geerlingguy/top500-benchmark/issues/4
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Project mention: 1.5 TB of VRAM on Mac Studio – RDMA over Thunderbolt 5 | news.ycombinator.com | 2025-12-18
See https://github.com/geerlingguy/beowulf-ai-cluster/issues/17 for more data — I didn't save all the prompt processing times (Exo just outputs a time in ms, no other data for that), but will try to have another pass. Maybe also convince the Exo team to add a proper benchmarking capability ala `llama-bench` :)
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jinja Cluster discussion
Jinja Cluster related posts
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Can Intel finally beat ARM on performance per Watt?
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1.5 TB of VRAM on Mac Studio – RDMA over Thunderbolt 5
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Ask HN: ARM workstations for homelab CPU based AI Inference testing?
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Everything I've learned building the fastest Arm desktop
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Automated Deployment of PostgreSQL Ha Clusters Anywhere
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This is what the next Mac Pro COULD be [Ampere Altra Developer Platform PC review]
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Toying with the idea of running Postgres instead of using RDS
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A note from our sponsor - SaaSHub
www.saashub.com | 12 Aug 2026
Index
What are some of the best open-source Cluster projects in Jinja? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | ansible-role-k3s | 714 |
| 2 | top500-benchmark | 398 |
| 3 | beowulf-ai-cluster | 374 |
| 4 | k8s-cluster-installation | 116 |
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