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For users

  • Getting Started
  • User Guide
    • Executors
    • Storage
    • Memory
    • Reliability
    • Optimization
    • Scaling
    • Diagnostics
    • GPU Support
  • Examples
    • How to run
    • Basic array operations
    • Zarr
    • Xarray
    • Rechunking
    • Icechunk
    • Pangeo
  • API Reference
    • cubed.Array
    • cubed.Array.compute
    • cubed.Array.rechunk
    • cubed.Array.visualize
    • cubed.compute
    • cubed.visualize
    • cubed.from_array
    • cubed.from_zarr
    • cubed.store
    • cubed.to_zarr
    • cubed.apply_gufunc
    • cubed.map_blocks
    • cubed.map_overlap
    • cubed.rechunk
    • cubed.isin
    • cubed.nanmean
    • cubed.nansum
    • cubed.pad
    • cubed.random.random
    • cubed.Callback
    • cubed.Spec
    • cubed.TaskEndEvent
    • cubed.measure_reserved_mem
    • cubed.raise_if_computes
  • Python Array API
  • Configuration
  • Why Cubed?
  • Related Projects
  • Articles and Presentations

For developers

  • Design
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User Guide

User Guide#

This guide introduces the concepts that will help you get the most out of Cubed.

  • Executors
    • Local single-machine executors
    • Which cloud service executor should I use?
    • Specifying an executor
  • Storage
    • Local storage
    • Cloud storage
    • Zarr storage libraries
  • Memory
    • Allowed memory
    • Projected memory
    • Reserved memory
    • Chunk sizes
  • Reliability
    • Strong consistency
    • Retries
    • Timeouts
    • Stragglers
  • Optimization
    • Map fusion
    • Multiple-input fusion
    • Debugging optimization
    • Advanced settings
  • Scaling
    • Preface: Types of Scaling
    • Theoretical vs Practical Scaling of Cubed
    • Other Performance Considerations
    • Diagnosing Performance
    • Tips
  • Diagnostics
    • Visualize the computation plan
    • Callbacks
    • Memray
  • GPU Support

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Getting Started

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Executors

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