pyiron/executorlib
Feb 2026 – Mar 2026
2 Months active
Languages Used
Python
Technical Skills
concurrent programmingjob schedulingresource managementthreadingHigh Performance ComputingPython
Ilgar Baghishov
PROFILE
Ilgar Baghishov
Worked on the pyiron/executorlib repository to enhance reliability and maintainability in high performance computing environments. Focused on improving worker job submission ordering and GPU resource allocation by introducing serialization and threading.Event synchronization, ensuring worker_id alignment with Flux scheduling. Addressed concurrency issues by enforcing sequential registration with the Flux broker, reducing failures from race conditions. Refactored dead worker handling into a dedicated helper function, simplifying the codebase and improving testability. Added unit tests to cover edge cases in task scheduling and resource management. Utilized Python and concurrent programming techniques to deliver robust solutions for job scheduling and worker management challenges.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
2Total
Bugs
2
Commits
2
Features
0
Lines of code
35,496
Activity Months2
Your Network
64 peopleShared Repositories
1
Work History
March 2026
1 Commits
Mar 1, 2026March 2026 monthly summary for developer work focusing on key accomplishments, with emphasis on reliability and maintainability improvements in the executor library.
1 Commits
Mar 1, 2026March 2026 monthly summary for developer work focusing on key accomplishments, with emphasis on reliability and maintainability improvements in the executor library.
March 2026
February 2026
1 Commits
Feb 1, 2026February 2026 monthly summary focused on reliability improvements for worker submissions and GPU resource mapping in the pyiron/executorlib subsystem. Implemented a robust fix set to ensure worker_id ordering aligns with Flux scheduling, improving resource allocation correctness and stability under concurrent workloads.
February 2026
1 Commits
Feb 1, 2026February 2026 monthly summary focused on reliability improvements for worker submissions and GPU resource mapping in the pyiron/executorlib subsystem. Implemented a robust fix set to ensure worker_id ordering aligns with Flux scheduling, improving resource allocation correctness and stability under concurrent workloads.
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
High Performance ComputingPythonTask Schedulingconcurrent programmingjob schedulingresource managementthreading
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