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Akanksha Gupta

PROFILE

Akanksha Gupta

Developed distributed initialization test coverage and metrics groundwork across GoogleCloudPlatform/ml-auto-solutions and AI-Hypercomputer repositories. Expanded JAX distributed.initialize() testing for TPU v4/v5p on GCE and GKE, supporting both single-slice and multi-slice configurations, and introduced a Bash-based test script for Airflow with robust exit-status handling. Leveraged Python and shell scripting to validate test reliability across nightly and stable CI builds, reducing flakiness and improving cross-repo testing. In AI-Hypercomputer/xpk, implemented environment variable configuration in workload.py to enable future Pathways metrics collection, aligning with broader observability goals. Focused on correctness, future compatibility, and seamless integration with existing cloud infrastructure.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

6Total
Bugs
0
Commits
6
Features
3
Lines of code
589
Activity Months2

Work History

March 2025

1 Commits • 1 Features

Mar 1, 2025

March 2025 (2025-03) focused on laying the foundations for Pathways metrics collection in AI-Hypercomputer/xpk, positioning the project for improved observability and data-driven optimization. The month delivered environment-configuration groundwork across the Pathways workload to enable metrics collection in future sprints, covering worker, rm, and proxy components in workload.py. No major bug fixes were completed this period; work emphasized correctness, future compatibility, and alignment with metrics initiatives.

November 2024

5 Commits • 2 Features

Nov 1, 2024

November 2024 performance summary: Expanded distributed initialization test coverage and stabilized test tooling across TPU platforms and CI environments. Key efforts include extending JAX distributed.initialize() tests to cover TPU v4/v5p across GCE and GKE (single-slice and multi-slice configurations with multiple test setups) and introducing a Bash-based test script for Airflow that verifies jax.distributed.initialize() with Python3 and robust exit-status reporting.

Activity

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Quality Metrics

Correctness81.6%
Maintainability80.0%
Architecture73.4%
Performance66.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

BashPython

Technical Skills

CI/CDCloud ComputingCloud EngineeringCloud InfrastructureCloud TestingDevOpsDistributed SystemsPythonShell ScriptingTPU TestingTesting

Repositories Contributed To

3 repos

Overview of all repositories you've contributed to across your timeline

GoogleCloudPlatform/ml-auto-solutions

Nov 2024 Nov 2024
1 Month active

Languages Used

Python

Technical Skills

CI/CDCloud ComputingCloud InfrastructureCloud TestingDistributed SystemsPython

AI-Hypercomputer/maxtext

Nov 2024 Nov 2024
1 Month active

Languages Used

BashPython

Technical Skills

Distributed SystemsPythonShell ScriptingTesting

AI-Hypercomputer/xpk

Mar 2025 Mar 2025
1 Month active

Languages Used

Python

Technical Skills

Cloud EngineeringDevOps