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Dylan Lim

PROFILE

Dylan Lim

Worked on the HazyResearch/ThunderKittens repository, delivering core GPU infrastructure for distributed and parallel computing. Over three months, developed and refactored APIs for device management, memory operations, and reduction primitives, focusing on compile-time safety and performance. Implemented vectorized and group-level operations across register, shared, and multi-device scopes, enabling efficient data movement and synchronization. Enhanced system stability by fixing memory issues, modernizing legacy code, and expanding test coverage. Leveraged C++, CUDA, and Python to build scalable, low-level features supporting large language models and deep learning workloads, while improving maintainability and developer productivity through code organization, profiling, and robust testing practices.

Overall Statistics

Feature vs Bugs

76%Features

Repository Contributions

88Total
Bugs
9
Commits
88
Features
28
Lines of code
20,060
Activity Months3

Work History

June 2025

9 Commits • 2 Features

Jun 1, 2025

June 2025 monthly highlights for HazyResearch/ThunderKittens: Fixed a critical build blocker, delivered cross-device data movement and reduction capabilities, and enhanced memory operation APIs, delivering measurable improvements in stability, scalability, and developer productivity.

April 2025

35 Commits • 12 Features

Apr 1, 2025

April 2025 (ThunderKittens): Delivered substantive vectorization, synchronization, and reliability improvements that accelerated large-scale workloads and improved model throughput, while expanding testing coverage and maintainability. The work focused on enabling efficient vector-level operations across register/shared/group/warp scopes, strengthening correctness under partial-barrier and mixed-partial scenarios, and laying groundwork for scalable future features.

March 2025

44 Commits • 14 Features

Mar 1, 2025

March 2025 performance highlights for HazyResearch/ThunderKittens. Delivered API modernization, performance-oriented enhancements, and stability improvements across GPU-related subsystems. Focus areas were API refactor and compile-time safety, all-reduce and multimem.red improvements, PGL-based operation paths, and robust device/testing support, driving business value through safer interfaces, lower latency, and improved resilience.

Activity

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Quality Metrics

Correctness88.8%
Maintainability85.6%
Architecture85.8%
Performance86.0%
AI Usage21.6%

Skills & Technologies

Programming Languages

C++CUDACudaMakefilePython

Technical Skills

BF16 Data TypeBuild SystemsC++C++ Template MetaprogrammingC++ templatesCUDACUDA ProgrammingCUDA programmingCode DocumentationCode OrganizationCode RefactoringCode refactoringDebuggingDeep LearningDevice Management

Repositories Contributed To

1 repo

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

HazyResearch/ThunderKittens

Mar 2025 Jun 2025
3 Months active

Languages Used

C++CUDACudaMakefilePython

Technical Skills

BF16 Data TypeC++C++ Template MetaprogrammingC++ templatesCUDACUDA Programming