EXCEEDS logo
Exceeds
Brian Tsoi

PROFILE

Brian Tsoi

Over four months, contributed to core Tenstorrent repositories including tt-xla, tt-forge, and tt-mlir, focusing on performance benchmarking, model deployment, and compiler robustness. Developed end-to-end benchmarking tools and expanded tensor parallel test suites using Python and C++, enabling comprehensive performance evaluation for models like Falcon, Llama, and Qwen. Enhanced system descriptor serialization and cross-system compilation, supporting hardware-agnostic workflows. Improved reliability through CI/CD integration with GitHub Actions, increasing test coverage and early issue detection. Addressed sharding and graph compatibility in MLIR, and fixed model-specific bugs in PyTorch examples, demonstrating depth in backend development, data processing, and software testing.

Overall Statistics

Feature vs Bugs

71%Features

Repository Contributions

15Total
Bugs
4
Commits
15
Features
10
Lines of code
2,251
Activity Months4

Work History

April 2026

1 Commits • 1 Features

Apr 1, 2026

2026-04 Monthly Summary (tt-xla) focusing on CI-driven test reliability and coverage for model validation.

March 2026

3 Commits • 2 Features

Mar 1, 2026

In March 2026, delivered measurement-focused capabilities and cross-system tooling, improved stability, and expanded test coverage across core TT components. Key outcomes include the introduction of VLLM benchmarking with config-driven tests, enhanced system descriptor handling for cross-system compilation, and a critical bug fix to shard status handling in the compiler frontend. Key accomplishments: implementation of vLLM benchmarks configured via VLLMBenchmarkConfig with tests for llama-3.2-3b and llama-3.2-3b-batch32; addition of system descriptor loading and compile-only mode to enable cross-system builds with hardware-agnostic descriptors; and a fix for shard status propagation in GSPMD graphs by constraining status application to public functions and reinstating updateShardStatusForResult for GSPMD graphs.

February 2026

6 Commits • 4 Features

Feb 1, 2026

February 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.

January 2026

5 Commits • 3 Features

Jan 1, 2026

January 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

Loading activity data...

Quality Metrics

Correctness97.4%
Maintainability84.0%
Architecture86.8%
Performance84.0%
AI Usage30.6%

Skills & Technologies

Programming Languages

C++MLIRPythonYAML

Technical Skills

AI Model DeploymentBenchmarkingC++C++ developmentCI/CDData ProcessingData ScienceDeep LearningGitHub ActionsJAXMLIRMachine LearningPerformance TestingPyTorchPython

Repositories Contributed To

3 repos

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

tenstorrent/tt-xla

Jan 2026 Apr 2026
4 Months active

Languages Used

PythonC++YAML

Technical Skills

Data ScienceDeep LearningMachine LearningPyTorchPythonperformance testing

tenstorrent/tt-forge

Jan 2026 Feb 2026
2 Months active

Languages Used

Python

Technical Skills

BenchmarkingMachine LearningPython DevelopmentPerformance TestingPython

tenstorrent/tt-mlir

Jan 2026 Mar 2026
2 Months active

Languages Used

C++MLIR

Technical Skills

C++ developmentMLIRcompiler designC++compiler development