Dask Working Notes
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Dask Working Notes

  • Improving GroupBy.map with Dask and Xarray: 21 Nov 2024
  • Dask DataFrame is Fast Now: 30 May 2024
  • High Level Query Optimization in Dask: 25 Aug 2023
  • Upstream testing in Dask: 18 Apr 2023
  • Do you need consistent environments between the client, scheduler and workers?: 14 Apr 2023
  • Deep Dive into creating a Dask DataFrame Collection with from_map: 12 Apr 2023
  • Shuffling large data at constant memory in Dask: 15 Mar 2023
  • Managing dask workloads with Flyte: 13 Feb 2023
  • Easy CPU/GPU Arrays and Dataframes: 02 Feb 2023
  • Dask Demo Day November 2022: 21 Nov 2022
  • Reducing memory usage in Dask workloads by 80%: 15 Nov 2022
  • Dask Kubernetes Operator: 09 Nov 2022
  • Understanding Dask’s meta keyword argument: 09 Aug 2022
  • Data Proximate Computation on a Dask Cluster Distributed Between Data Centres: 19 Jul 2022
  • Documentation Framework: 15 Jul 2022
  • How to run different worker types with the Dask Helm Chart: 17 Feb 2022
  • Reflections on one year as the Dask life science fellow: 15 Dec 2021
  • Mosaic Image Fusion: 01 Dec 2021
  • Choosing good chunk sizes in Dask: 02 Nov 2021
  • CZI EOSS Update: 20 Oct 2021
  • 2021 Dask User Survey: 15 Sep 2021
  • Google Summer of Code 2021 - Dask Project: 23 Aug 2021
  • High Level Graphs update: 07 Jul 2021
  • Ragged output, how to handle awkward shaped results: 02 Jul 2021
  • Dask Down Under: 25 Jun 2021
  • Dask Survey 2021, early anecdotes: 18 Jun 2021
  • The evolution of a Dask Distributed user: 01 Jun 2021
  • The 2021 Dask User Survey is out now: 25 May 2021
  • Life sciences at the 2021 Dask Summit: 24 May 2021
  • Stability of the Dask library: 21 May 2021
  • Skeleton analysis: 07 May 2021
  • Dask with PyTorch for large scale image analysis: 29 Mar 2021
  • Image segmentation with Dask: 19 Mar 2021
  • Measuring Dask memory usage with dask-memusage: 11 Mar 2021
  • Getting to know the life science community: 04 Mar 2021
  • Dask User Summit 2021: 03 Mar 2021
  • Image Analysis Redux: 12 Nov 2020
  • 2020 Dask User Survey: 22 Sep 2020
  • Announcing the DaskHub Helm Chart: 31 Aug 2020
  • Running tutorials: 21 Aug 2020
  • Comparing Dask-ML and Ray Tune's Model Selection Algorithms: 06 Aug 2020
  • Configuring a Distributed Dask Cluster: 30 Jul 2020
  • The current state of distributed Dask clusters: 23 Jul 2020
  • Faster Scheduling: 21 Jul 2020
  • Last Year in Review: 17 Jul 2020
  • Large SVDs: 13 May 2020
  • Dask Summit: 28 Apr 2020
  • Estimating Users: 14 Jan 2020
  • Dask Deployment Updates: 01 Nov 2019
  • DataFrame Groupby Aggregations: 08 Oct 2019
  • Better and faster hyperparameter optimization with Dask: 30 Sep 2019
  • Co-locating a Jupyter Server and Dask Scheduler: 13 Sep 2019
  • Dask on HPC: a case study: 28 Aug 2019
  • Dask and ITK for large scale image analysis: 09 Aug 2019
  • 2019 Dask User Survey: 05 Aug 2019
  • Dask Release 2.2.0: 02 Aug 2019
  • Extracting fsspec from Dask: 23 Jul 2019
  • Dask Release 2.0: 22 Jun 2019
  • Load Large Image Data with Dask Array: 20 Jun 2019
  • Python and GPUs: A Status Update: 19 Jun 2019
  • Dask on HPC: 12 Jun 2019
  • Experiments in High Performance Networking with UCX and DGX: 09 Jun 2019
  • Composing Dask Array with Numba Stencils: 09 Apr 2019
  • cuML and Dask hyperparameter optimization: 27 Mar 2019
  • Dask and the __array_function__ protocol: 18 Mar 2019
  • Building GPU Groupby-Aggregations for Dask: 04 Mar 2019
  • Running Dask and MPI programs together: 31 Jan 2019
  • Single-Node Multi-GPU Dataframe Joins: 29 Jan 2019
  • Dask Release 1.1.0: 23 Jan 2019
  • Extension Arrays in Dask DataFrame: 22 Jan 2019
  • Dask, Pandas, and GPUs: first steps: 13 Jan 2019
  • GPU Dask Arrays, first steps: 03 Jan 2019
  • Dask Version 1.0: 29 Nov 2018
  • Dask-jobqueue: 08 Oct 2018
  • Refactor Documentation: 27 Sep 2018
  • Dask Development Log: 17 Sep 2018
  • Dask Release 0.19.0: 05 Sep 2018
  • High level performance of Pandas, Dask, Spark, and Arrow: 28 Aug 2018
  • Building SAGA optimization for Dask arrays: 07 Aug 2018
  • Dask Development Log: 02 Aug 2018
  • Pickle isn't slow, it's a protocol: 23 Jul 2018
  • Dask Development Log, Scipy 2018: 17 Jul 2018
  • Who uses Dask?: 16 Jul 2018
  • Dask Development Log: 08 Jul 2018
  • Dask Scaling Limits: 26 Jun 2018
  • Dask Release 0.18.0: 14 Jun 2018
  • Beyond Numpy Arrays in Python: 27 May 2018
  • Dask Release 0.17.2: 21 Mar 2018
  • Craft Minimal Bug Reports: 28 Feb 2018
  • Dask Release 0.17.0: 12 Feb 2018
  • Credit Modeling with Dask: 09 Feb 2018
  • Pangeo: JupyterHub, Dask, and XArray on the Cloud: 22 Jan 2018
  • Dask Development Log: 06 Dec 2017
  • Dask Release 0.16.0: 21 Nov 2017
  • Optimizing Data Structure Access in Python: 03 Nov 2017
  • Streaming Dataframes: 16 Oct 2017
  • Notes on Kafka in Python: 10 Oct 2017
  • Dask Release 0.15.3: 24 Sep 2017
  • Fast GeoSpatial Analysis in Python: 21 Sep 2017
  • Dask on HPC - Initial Work: 18 Sep 2017
  • Dask Release 0.15.2: 30 Aug 2017
  • Scikit-Image and Dask Performance: 18 Jul 2017
  • Dask Benchmarks: 03 Jul 2017
  • Use Apache Parquet: 28 Jun 2017
  • Dask Release 0.15.0: 15 Jun 2017
  • Dask Release 0.14.3: 08 May 2017
  • Dask Development Log: 28 Apr 2017
  • Asynchronous Optimization Algorithms with Dask: 19 Apr 2017
  • Dask and Pandas and XGBoost: 28 Mar 2017
  • Dask Release 0.14.1: 23 Mar 2017
  • Developing Convex Optimization Algorithms in Dask: 22 Mar 2017
  • Dask Release 0.14.0: 27 Feb 2017
  • Dask Development Log: 20 Feb 2017
  • Experiment with Dask and TensorFlow: 11 Feb 2017
  • Two Easy Ways to Use Scikit Learn and Dask: 07 Feb 2017
  • Dask Development Log: 30 Jan 2017
  • Custom Parallel Algorithms on a Cluster with Dask: 24 Jan 2017
  • Dask Development Log: 18 Jan 2017
  • Distributed NumPy on a Cluster with Dask Arrays: 17 Jan 2017
  • Distributed Pandas on a Cluster with Dask DataFrames: 12 Jan 2017
  • Dask Release 0.13.0: 03 Jan 2017
  • Dask Development Log: 24 Dec 2016
  • Dask Development Log: 18 Dec 2016
  • Dask Development Log: 12 Dec 2016
  • Dask Development Log: 05 Dec 2016
  • Dask Cluster Deployments: 22 Sep 2016
  • Dask and Celery: 13 Sep 2016
  • Dask Distributed Release 1.13.0: 12 Sep 2016
  • Dask for Institutions: 16 Aug 2016
  • Dask and Scikit-Learn -- Model Parallelism: 12 Jul 2016
  • Ad Hoc Distributed Random Forests: 20 Apr 2016
  • Fast Message Serialization: 14 Apr 2016
  • Distributed Dask Arrays: 26 Feb 2016
  • Pandas on HDFS with Dask Dataframes: 22 Feb 2016
  • Introducing Dask distributed: 17 Feb 2016
  • Dask is one year old: 21 Dec 2015
  • Distributed Prototype: 09 Oct 2015
  • Caching: 03 Aug 2015
  • Custom Parallel Workflows: 23 Jul 2015
  • Write Complex Parallel Algorithms: 26 Jun 2015
  • Distributed Scheduling: 23 Jun 2015
  • State of Dask: 19 May 2015
  • Towards Out-of-core DataFrames: 11 Mar 2015
  • Towards Out-of-core ND-Arrays -- Dask + Toolz = Bag: 17 Feb 2015
  • Towards Out-of-core ND-Arrays -- Slicing and Stacking: 13 Feb 2015
  • Towards Out-of-core ND-Arrays -- Spilling to Disk: 16 Jan 2015
  • Towards Out-of-core ND-Arrays -- Benchmark MatMul: 14 Jan 2015
  • Towards Out-of-core ND-Arrays -- Multi-core Scheduling: 06 Jan 2015
  • Towards Out-of-core ND-Arrays -- Frontend: 30 Dec 2014
  • Towards Out-of-core ND-Arrays: 27 Dec 2014

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