
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.
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.
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 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 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: 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.
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.
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.
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.
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.
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: 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.
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.
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.
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.

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