Conversation
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@timfel What do you think? It mostly worked: It was extremely slow: I cancelled it after an hour. Is it premature? Does it require much more powerful runner? |
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@maurycy we run the pyperformance benchmarks internally, but they require a powerful runner and lots more warmup than PyPy or CPython per benchmark. One hour is not nearly enough, we give it 18 cores and 64G of RAM and it runs in about 2.5 hours |
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As for the benchmarks, the networkx benchmarks should work, that's a bug on our side. But dask and gc_collect as are won't, the GC benchmarks in general just don't make much sense on GraalPy, since we have a completely different GC, so neither the benchmark nor any assertions make sense for us. The dask one doesn't work because we don't support the |
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This also increases the CI runs from around 13 minutes to over 2.5 hours. |
That was just tests, though: Other tests finished in ~10 minutes FYI: The whole benchmark runs in ~1h on cpython on i9-12900K, 128G DDR4 |
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@maurycy if it's anything like in our internal setup, running the pip subprocesses to install dependencies is easily the worst part of the runtime. These |
It's an alternative Python implementation, as per python/pythondotorg#2797 and supported by https://github.com/actions/setup-python