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Dagger.jl is a framework for out-of-core and parallel computing in Julia that allows users to construct and execute dynamic task graphs. It is designed for large-scale, distributed, and memory-efficient computations. Dagger supports lazy evaluation and scheduling across multiple threads or machines, enabling high-performance workflows for data processing, scientific computing, and machine learning.
Features
- Constructs dynamic acyclic computation graphs
- Enables parallel and distributed execution
- Supports lazy evaluation for memory efficiency
- Integrates with multi-threading and cluster environments
- Handles out-of-core computations for large datasets
- Interoperable with Julia arrays, tables, and custom types
Project Samples
Categories
Computational Fluid Dynamics (CFD)License
MIT LicenseFollow Dagger.jl
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