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Mahdieh Ghazi

PROFILE

Mahdieh Ghazi

Over four months, contributed to the microsoft/mscclpp repository by developing advanced GPU and network features for high-performance computing. Delivered FP8 data type support and architecture-aware optimizations using C++ and CUDA, enabling higher throughput on newer NVIDIA GPUs while maintaining broad hardware compatibility. Built an inter-node switch channel performance testing harness to validate and benchmark multi-node GPU communication, leveraging CUDA and Makefile-based workflows. Released version 0.9.0, ensuring clear versioning and packaging readiness. Added Multi-path Reliable Connection support through CMake configuration and network programming, enhancing network resilience and performance. Focused on robust, portable solutions with streamlined build and deployment processes.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

5Total
Bugs
0
Commits
5
Features
4
Lines of code
352
Activity Months4

Your Network

4942 people

Work History

May 2026

1 Commits • 1 Features

May 1, 2026

May 2026 monthly summary focused on delivering Multi-path Reliable Connection (MRC) support for the MSCCL++ library in the microsoft/mscclpp repo. Achieved groundwork for multi-path connectivity, performance improvements, and network resilience through new build/configuration options and updates to the ibverbs wrapper to accommodate MRC functionality. Implemented necessary macros and instructions to enable MRC with no atomic, aligning with low-latency, high-throughput goals while keeping compatibility with existing pipelines.

April 2026

1 Commits • 1 Features

Apr 1, 2026

For 2026-04, delivered the Version 0.9.0 software release for microsoft/mscclpp by bumping from 0.8.0 and updating the VERSION file. Key commit: e66ce39647a3db04b6996d7d3c53bc18c0201488 documents the version update. No major bugs fixed this month. The release adds packaging readiness and sets the project on the 0.9.0 release track, aligning with the roadmap and enabling downstream integration and customer delivery.

February 2026

1 Commits • 1 Features

Feb 1, 2026

Concise monthly summary for 2026-02 focusing on microsoft/mscclpp: Key feature delivered: - Inter-node Switch Channel Performance Testing harness: Added an end-to-end example codebase for testing switch channel functionality in both single-node and multi-node environments. Includes a Makefile and a CUDA source file, enabling performance evaluation and validation of inter-node communication. Major fixes (if any): - No explicit bug fixes reported for this repo this month. Overall impact and accomplishments: - Established a repeatable performance testing workflow for inter-node switch channels, enabling faster benchmarking and validation of communication paths across GPUs and nodes. This supports performance tuning and reliability for multi-node workloads. - The work lays groundwork for more comprehensive documentation and algorithm-level explanations in a future PR, improving learnability and auditability. Technologies/skills demonstrated: - CUDA-based performance testing, Makefile-based build orchestration, multi-node testing patterns, basic benchmarking and result interpretation, evidence-driven development. Referenced commit: - 2a6f1c11927389bcee3398e0a43384aa3eb98e5e ("Mahdieh/switchchannel test clean (#751)") which adds the example code and tests for switch channel functionality across single and multi-node environments.

January 2026

2 Commits • 1 Features

Jan 1, 2026

Month 2026-01: Delivered FP8 data type support in NVLS and architecture-aware MSCCL++ optimizations for microsoft/mscclpp, enabling meaningful performance gains on newer NVIDIA GPUs. Implemented architecture auto-detection to select native CUDA architectures when an NVIDIA GPU is present, with a multi-arch fallback for portability. FP8 paths are auto-enabled for a-series GPUs (e.g., sm_100a), ensuring optimized code paths where supported. Improved build-paths and clarified FP8-related build flags in CMake (-MSCCLPP_GPU_ARCHS) to reduce configuration errors and streamline deployments. This work establishes higher-throughput workloads with FP8 while maintaining broad hardware support and simpler CI/build processes.

Activity

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Quality Metrics

Correctness96.0%
Maintainability84.0%
Architecture92.0%
Performance92.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++CMakeCUDANone

Technical Skills

C++ DevelopmentC++ developmentCMakeCMake configurationCUDAGPU ProgrammingGPU programmingNetwork programmingParallel ComputingPerformance Optimizationversion control

Repositories Contributed To

1 repo

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

microsoft/mscclpp

Jan 2026 May 2026
4 Months active

Languages Used

C++CMakeCUDANone

Technical Skills

CMakeCUDAGPU ProgrammingGPU programmingPerformance OptimizationC++ Development