google/deepvariant
Nov 2024 – Nov 2024
1 Month active
Languages Used
BUILDC++PythonPython (pybind)Shell
Technical Skills
BazelBioinformaticsBuild System ConfigurationC++C++ DevelopmentDependency Management
mobinasri
PROFILE
Mobinasri
Mobin Asri enhanced the google/deepvariant repository by implementing shared memory loading for GBZ pangenome workflows, focusing on memory efficiency and multi-process data access. Using C++, Python, and Bazel, Mobin introduced a guarded shared memory mechanism with a default 12GB allocation, while adding a configurable flag to disable shared memory by default to maintain workflow stability. The work included updating core dependencies such as gbwt and sdsl_lite to improve compatibility and performance. By storing the graph index in shared memory, Mobin reduced memory usage per shard and refined default behaviors for pangenome-aware workflows, demonstrating depth in system design and optimization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
607
Activity Months1
Your Network
4166 people
Work History
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 performance highlights for google/deepvariant focused on GBZ pangenome workflows and memory efficiency. Implemented guarded shared memory loading for GBZ sequences with a default 12GB shared memory size to accelerate multi-process data access, and added a configurable flag to disable shared memory by default to preserve stability and compatibility. Updated core dependencies (gbwt and sdsl_lite) to newer versions to improve compatibility and potential memory/performance characteristics. Introduced a shared-memory index for the graph, delivering approximately 0.6GB memory reduction per shard. Resolved a GBZ reader memory issue and refined defaults for pangenome-aware DV workflows when gbz format is present. The GBZ reader now defaults to not using shared memory unless explicitly enabled, improving stability for existing workflows. Overall, these changes reduce memory footprint, improve throughput for large-scale pangenome analyses, and simplify integration with evolving workflows.
4 Commits • 2 Features
Nov 1, 2024November 2024 performance highlights for google/deepvariant focused on GBZ pangenome workflows and memory efficiency. Implemented guarded shared memory loading for GBZ sequences with a default 12GB shared memory size to accelerate multi-process data access, and added a configurable flag to disable shared memory by default to preserve stability and compatibility. Updated core dependencies (gbwt and sdsl_lite) to newer versions to improve compatibility and potential memory/performance characteristics. Introduced a shared-memory index for the graph, delivering approximately 0.6GB memory reduction per shard. Resolved a GBZ reader memory issue and refined defaults for pangenome-aware DV workflows when gbz format is present. The GBZ reader now defaults to not using shared memory unless explicitly enabled, improving stability for existing workflows. Overall, these changes reduce memory footprint, improve throughput for large-scale pangenome analyses, and simplify integration with evolving workflows.
November 2024
Activity
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Quality Metrics
Correctness82.6%
Maintainability80.0%
Architecture82.6%
Performance85.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BUILDC++PythonPython (pybind)Shell
Technical Skills
BazelBioinformaticsBuild System ConfigurationC++C++ DevelopmentDependency ManagementDevOpsDockerGenomicsMemory ManagementPerformance OptimizationPythonPython DevelopmentPython ScriptingShared Memory
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