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Achievement: Pull Shark

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Achievement: Pull Shark

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@juandavid-guerrero

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divadnauj-GB/README.md

Hi there 👋

Welcome to my page; here, you can find most of the repositories I am working on. The repositories comprise a wide spectrum of flavors, including but not limited to:

  • Advanced digital design for FPGAs
  • Computational arithmetic for AI
  • Accelerators for vision applications
  • Functional in-field testing of hardware components (e.g., CPUs, and GPUs)
  • Dependability and fault tolerance for AI accelerators
  • AI reliability assessment (i.e., error modeling of hardware faults).

I encourage you to have a look at my work and feel free to contact me for queries, suggestions, or comments that can help to improve the work available here 😊.

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  1. stereo_vision_core stereo_vision_core Public

    Stereo Vision Core accelerator is a real-time stream processing architecture that calculates the disparity map of stereo images. The accelerator is available as an RTL description using VHDL, which…

    VHDL 1

  2. nvbitPERfi nvbitPERfi Public

    C 4 3

  3. Jerc007/Open-GPGPU-FlexGrip- Jerc007/Open-GPGPU-FlexGrip- Public

    FlexGripPlus: an open-source GPU model for reliability evaluation and micro architectural simulation

    VHDL 94 19

  4. edwar-vhd/SFU-Piecewise-Polynomial-Approximation edwar-vhd/SFU-Piecewise-Polynomial-Approximation Public

    Special Function Units (SFUs) are hardware accelerators, their implementation helps improve the performance of GPUs to process some of the most complex operations. This SFU implements the Piecewise…

    VHDL 7 1

  5. TheColombianTeam/GPUScheduling TheColombianTeam/GPUScheduling Public

    Python

  6. GPU-programming-2024-25 GPU-programming-2024-25 Public

    This repository contains the laboratory exercises of the 2024/25 course of GPU programming course at Politecnico di Torino.

    Cuda 1