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Hello,
I'm considering using MeTTa for a conversational AI application and have some questions about its performance with large datasets.
In the OpenCog Atomspace Metagraphs paper, it's mentione…
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When restarting a cluster of Nannies we expect every worker to be restarted and connect to the worker.
There appears to exist a race condition where the worker instead closes for good and tears dow…
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Spark 3.1
Delta
참고자료
- https://databricks.com/blog/2021/03/02/introducing-apache-spark-3-1.html
- https://databricks.com/session_na21/deep-dive-into-the-new-features-of-apache-spark-3-1
- htt…
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### What happened?
When using `rolling(...).construct(...) in https://github.com/coiled/benchmarks/pull/1552, I noticed that my Dask workers died running out of memory because the chunk sizes get b…
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### 🐛 Describe the bug
Hello, I am training OPT model on the A100 GPUs. I found it used 76GB GPU memory when I use `auto` mode and set `gpu_margin_mem_ratio` as 0. If I use `cpu` mode, it only take…
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In the monthly Dask community meeting today @martindurant mentioned he wanted to see what impact his shared memory PR (xref https://github.com/dask/distributed/pull/6503) has on the benchmarks here.
…
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Imported from SourceForge on 2024-07-04 22:13:57
Created by **[lc1](https://sourceforge.net/u/lc1/)** on 2013-11-04 22:12:40
Original: https://sourceforge.net/p/maxima/bugs/2657
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Maxima 5.31.1 ht…
rtoy updated
4 months ago
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I have been running full size Pangeo Forge recipes on [Pangeo Cloud](https://pangeo.io/cloud.html), using Dask Gateway clusters of 10-50 workers. This has been a good opportunity to see how things per…
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I love the xgboost distribution package and what it enables, however when dealing with datasets or trees that do not fit into memory one needs to scale the task using a distributed framework like dask…
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I am trying to do data analysis on the 9900 parquet files that in total they have 100GB size.
After 70K garbage collections warning:
`distributed.utils_perf - WARNING - full garbage collections …