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Jakub Szuppe

PROFILE

Jakub Szuppe

Over seven months, Jakub Szuppe developed and maintained advanced GPU math and FFT sample workflows in the NVIDIA/CUDALibrarySamples repository, focusing on onboarding and integration for CUDA-based libraries. He delivered end-to-end examples and documentation for cuFFTDx, cuBLASDx, and MathDx, using C++, CUDA, and CMake to ensure reproducible builds and compatibility across environments. Jakub’s work included detailed sample code for 1D, 2D, and 3D FFTs, GEMM, and batched operations, along with robust documentation updates and build system improvements. His contributions emphasized clarity, maintainability, and alignment with evolving library versions, reducing onboarding friction and supporting reliable GPU-accelerated workflows.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

11Total
Bugs
0
Commits
11
Features
9
Lines of code
24,651
Activity Months7

Work History

January 2026

1 Commits • 1 Features

Jan 1, 2026

January 2026 monthly summary for NVIDIA/CUDALibrarySamples: Delivered a versioned update to MathDx Samples (25.12.1) with enhanced documentation and new advanced GPU math examples, ensuring alignment with the latest API and reducing onboarding time for developers.

February 2025

1 Commits • 1 Features

Feb 1, 2025

February 2025 monthly summary for NVIDIA/CUDALibrarySamples: Focused on updating documentation and build configuration for MathDx libraries to support the new 25.01 package and new examples. Prepared clearer READMEs, added new examples for cuBLASDx, cuSolverDx, and cuRANDDx, and updated CMakeLists.txt to reference package version 25.01.

February 2024

2 Commits • 1 Features

Feb 1, 2024

February 2024: Focused on CuFFTDx usability for NVIDIA/CUDALibrarySamples. Delivered a comprehensive set of FFT and convolution examples along with a dedicated README to improve onboarding and API usage. Commits included two updates: adding all cuFFTDx 1.1.1 examples and creating a cuFFTDx examples README. No major bugs fixed this period; the emphasis was on documentation and sample code to reduce onboarding friction and support requests. Impact includes faster customer integration, clearer usage guidance, and reduced time-to-value for new users. Technologies demonstrated include CUDA/C++ example development, documentation tooling, and version-control discipline aligned with CuFFTDx 1.1.1 feature delivery.

January 2024

1 Commits • 1 Features

Jan 1, 2024

2024-01 Monthly Summary: Focused on delivering cuBLASDx demonstration samples in the NVIDIA/CUDALibrarySamples repository, with performance benchmarks and clear usage scenarios for GEMM, FFT, and Batched GEMM. This work enhances developer onboarding, accelerates evaluation of cuBLASDx, and provides tangible references for integration into GPU-accelerated pipelines.

January 2023

2 Commits • 2 Features

Jan 1, 2023

Month: 2023-01 — NVIDIA/CUDALibrarySamples focused on enhancing FFT tutorial depth and code quality for 2D/3D operations. Delivered targeted documentation improvements and more robust, maintainable example code, resulting in clearer guidance, better testing instrumentation, and more accurate results verification. This aligns with business goals to reduce onboarding effort and improve user confidence in cuFFT-based workflows.

December 2022

3 Commits • 2 Features

Dec 1, 2022

December 2022: Expanded cuFFTDx sample coverage in NVIDIA/CUDALibrarySamples and hardened cross-environment builds. Delivered new 2D/3D FFT examples with single-kernel and shared-memory variants, plus build and compatibility improvements to support newer CUDA architectures and MSVC environments, reducing integration effort and improving user onboarding.

April 2022

1 Commits • 1 Features

Apr 1, 2022

Month: 2022-04. Delivered a concrete feature in NVIDIA/CUDALibrarySamples: a 'Hello World' sample for cuFFTDx 1024-point complex-to-complex FFT, with clear build/run instructions and a dedicated commit. This work provides a ready-to-run demonstration of cuFFTDx capabilities and establishes a template for future performance benchmarks. No major bugs fixed this month. Impact includes improved developer onboarding, faster validation of cuFFTDx in CUDA workflows, and a reproducible FFT workflow. Technologies demonstrated include CUDA programming, cuFFTDx usage, and repository contribution workflows.

Activity

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Quality Metrics

Correctness96.4%
Maintainability89.0%
Architecture96.4%
Performance89.0%
AI Usage23.6%

Skills & Technologies

Programming Languages

C++CMakeCUDAMarkdown

Technical Skills

API usageBuild SystemsC++C++ developmentCMakeCUDACUDA programmingDocumentationFFT AlgorithmsFFT algorithmsGPU ProgrammingGPU computingMathematical LibrariesMatrix operationsNumerical Methods

Repositories Contributed To

1 repo

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

NVIDIA/CUDALibrarySamples

Apr 2022 Jan 2026
7 Months active

Languages Used

C++CMakeCUDAMarkdown

Technical Skills

CUDAFFT AlgorithmsGPU ProgrammingBuild SystemsCMakeCUDA programming