tenstorrent/tt-xla
Jan 2026 – Feb 2026
2 Months active
Languages Used
Python
Technical Skills
Data ScienceDeep LearningMachine LearningPyTorchPythonperformance testing
Brian Tsoi
PROFILE
Brian Tsoi
During a two-month period, Brian Tsoi developed and stabilized advanced benchmarking and model deployment features across the tenstorrent/tt-xla, tt-forge, and tt-mlir repositories. He implemented end-to-end performance benchmarking and expanded tensor parallel testing for models like Falcon, Llama, and Qwen, using C++ and Python to enhance performance visibility and evaluation. Brian introduced new graph compatibility passes in MLIR, improved sharding robustness, and enabled system descriptor serialization for better workflow reliability. His work included fixing model import paths and tensor shape handling, demonstrating depth in backend development, data processing, and software testing while addressing both feature delivery and stability improvements.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
11Total
Bugs
3
Commits
11
Features
7
Lines of code
1,165
Activity Months2
Your Network
455 peopleWork History
February 2026
6 Commits • 4 Features
Feb 1, 2026February 2026 monthly recap: Delivered notable features and stability fixes across tt-forge and tt-xla that enhance performance evaluation, onboarding, and reliability for large-model workflows. Key achievements include expanding the TP Benchmark Suite, shipping a ready-to-run gpt-oss-20b generative example, enabling system descriptor persistence, and introducing MLACache validation tests, along with sharding robustness fixes to support variable tensor shapes.
6 Commits • 4 Features
Feb 1, 2026February 2026 monthly recap: Delivered notable features and stability fixes across tt-forge and tt-xla that enhance performance evaluation, onboarding, and reliability for large-model workflows. Key achievements include expanding the TP Benchmark Suite, shipping a ready-to-run gpt-oss-20b generative example, enabling system descriptor persistence, and introducing MLACache validation tests, along with sharding robustness fixes to support variable tensor shapes.
February 2026
January 2026
5 Commits • 3 Features
Jan 1, 2026January 2026 monthly highlights focusing on performance visibility, benchmarking expansion, and XLA graph compatibility across the TT stack. Delivered concrete features, stabilized key workflows, and broadened benchmarking coverage to accelerate performance-driven decisions for model deployment and development.
January 2026
5 Commits • 3 Features
Jan 1, 2026January 2026 monthly highlights focusing on performance visibility, benchmarking expansion, and XLA graph compatibility across the TT stack. Delivered concrete features, stabilized key workflows, and broadened benchmarking coverage to accelerate performance-driven decisions for model deployment and development.
Activity
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Quality Metrics
Correctness98.2%
Maintainability85.4%
Architecture85.4%
Performance85.4%
AI Usage31.0%
Skills & Technologies
Programming Languages
C++MLIRPython
Technical Skills
AI Model DeploymentBenchmarkingC++ developmentData ProcessingData ScienceDeep LearningMLIRMachine LearningPerformance TestingPyTorchPythonPython DevelopmentSerializationTensorFlowTesting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
tenstorrent/tt-forge
Jan 2026 – Feb 2026
2 Months active
Languages Used
Python
Technical Skills
BenchmarkingMachine LearningPython DevelopmentPerformance TestingPython
tenstorrent/tt-mlir
Jan 2026 – Jan 2026
1 Month active
Languages Used
C++MLIR
Technical Skills
C++ developmentMLIRcompiler design