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CUDA Basics for Hackers, Part 1: Getting Started
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CUDA Basics for Hackers, Part 1: Getting Started

First part of a Hackers-Arise series teaching CUDA (NVIDIA Compute Unified Device Architecture): installing the CUDA toolkit and nvcc compiler on Kali or Debian-based Linux, writing a basic CUDA C++ kernel, and compiling and running a simple parallel vector-addition program. It explains GPU threading concepts (kernels, thread blocks, grids) and frames CUDA as foundational to AI workloads and to future security applications like password cracking, real-time threat detection and post-quantum cryptography, though those applications are only listed, not demonstrated, here.

TL;DR Step by step intro to installing CUDA and writing a first GPU kernel, pitched as groundwork for security uses like password cracking.
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What it is

This is the actual install command and compile/run workflow for Part 1 of a CUDA tutorial series, not just the topic framing. It targets Kali/Debian Linux with an NVIDIA GPU.

What to do

Install the toolkit and compiler:

sudo apt install nvidia-cuda-toolkit -y
nvcc --version

Write a .cu file (example used: hackers_arise_vector_cuda.cu), then compile:

nvcc hackers_arise_vector_cuda.cu -o myfirstcuda.cu

and run the resulting binary. The example program is a vector-addition kernel that: allocates host (CPU) and device (GPU) memory, copies input arrays host→device, launches a kernel configured with 256 threads per block (block count computed from array size), each thread computing a global thread ID with boundary checking, synchronizes before copying results device→host, verifies by printing the first 5 values, then frees all allocated memory.

Preconditions / Affected

Requires an actual NVIDIA GPU with CUDA support — this won't run without compatible hardware. Confirmed working on Kali/Debian-based distros via apt.

Caveats

The page notes a typo in its own run command (,/myfirstcuda.cu instead of ./myfirstcuda.cu). The listed security use cases (password cracking, threat detection, post-quantum crypto, phishing/malware analysis, network graph analysis) remain unlisted-only claims with no code or benchmarks in this installment — confirmed by the existing summary, not new information here.

Technologies named here

Techniques named here

  • GPU-accelerated password cracking and brute-force attacks
  • GPU-accelerated real-time threat detection
  • GPU-accelerated phishing and malware analysis
  • GPU-accelerated post-quantum cryptography
  • GPU-accelerated network graph analysis

Also named here

  • Master OTW

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