Charm4Py: Revolutionizing High-Performance Computing with Python Integration
"Charm4Py bridges the gap between high-performance computing and Python, offering a productive and efficient platform for distributed execution. Explore the seamless integration, productivity, and performance provided by Charm4Py in leveraging Charm++ with Python's rich ecosystem."
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Presentation Transcript
Charm4Py 1
Python Massive success in data science, ML Recent attention by HPC community Productive language to glue together hot code paths Written in C/C++, JIT-compiled to heterogeneous devices 3
Charm4Py Productivity + performance: Distributed execution of Charm++ with rich software ecosystem of Python 4
Charm4Py Basics Define chare classes in Python Create a main driver that creates chares, begins execution. That s it! No opaque compile errors, no additional files required 5
Overview Numpy, Pandas, Scipy Numba, PyCUDA User Code Runtime Python/C Interaction Charm++ Runtime 8
Arrays: Reductions, Load Balancing No need to define a PUP! Pickle is used 16
Channels Point-to-point communication channel between chares 17
Channels Point-to-point communication channel between chares 18
Channels Point-to-point communication channel between chares 19
Reductions: Targeting Futures Main chare: 22
Running Programs On your local machine 23
Running Programs On your local machine 24
Running Programs On your local machine On a cluster 25
Running Programs On your local machine On a cluster 26
More Information Source: https://github.com/UIUC-PPL/charm4py Docs: https://charm4py.readthedocs.io/en/latest/ 27
