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Sample: FFT Signal Analysis (Python)

python/2_CoreConcepts/fftSignalAnalysis/README.md

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Sample: FFT Signal Analysis (Python)

Description

Analyze signal frequencies using Fast Fourier Transform (FFT) on the GPU. This sample demonstrates CuPy's cuFFT for GPU-accelerated frequency analysis: generating composite signals, computing magnitude spectrum, detecting dominant frequencies via peak detection, and comparing GPU vs CPU FFT performance.

What You'll Learn

  • Using CuPy's cp.fft.rfft() for real-to-complex FFT on GPU
  • Computing magnitude spectrum from FFT results
  • Peak detection to identify dominant frequencies
  • Comparing GPU (cuFFT) vs CPU (NumPy) FFT performance
  • Uses cuda.core APIs for device management and CUDA event timing

Key Concepts

  • FFT (Fast Fourier Transform): Efficiently computes the Discrete Fourier Transform
  • Magnitude Spectrum: |FFT(signal)| * 2 / N gives amplitude at each frequency
  • rfft: Real FFT - optimized for real-valued input signals
  • Peak Detection: Finding local maxima to identify dominant frequencies

Stream Interop

This sample demonstrates CuPy integration with cuda.core streams:

python
# Create stream with cuda.core
stream = device.create_stream()

# Use with CuPy operations
cp.cuda.Stream.from_external(stream).use()

Key APIs

From cuda.core:

  • Device - Device management and context
  • EventOptions - Configure events for GPU timing
  • stream.record() - Record events for timing

From CuPy:

  • cp.fft.rfft() - Real-to-complex FFT (GPU-accelerated via cuFFT)
  • cp.fft.rfftfreq() - Generate frequency bins for rfft
  • cp.cuda.Stream.from_external() - Interop with cuda.core streams

From NumPy:

  • np.fft.rfft() - CPU FFT for comparison

Requirements

Hardware:

  • NVIDIA GPU with CUDA support

Software:

  • CUDA Toolkit 13.0 or newer
  • Python 3.10 or newer
  • See requirements.txt for Python packages

Installation

bash
pip install -r requirements.txt

How to Run

bash
python fftSignalAnalysis.py

Expected Output

============================================================
FFT Signal Analysis
============================================================

Device: <Your GPU>
Compute Capability: sm_XX

Signal Parameters:
  Samples: 1,048,576
  Sample Rate: 44,100 Hz
  ...

------------------------------------------------------------
GPU FFT (cuFFT)
------------------------------------------------------------
Time: X.XXX ms

Detected Frequencies:
     440.0 Hz (magnitude: X.XXXX)
     ...

------------------------------------------------------------
CPU FFT (NumPy)
------------------------------------------------------------
Time: XX.XXX ms

------------------------------------------------------------
PERFORMANCE SUMMARY
------------------------------------------------------------
GPU (cuFFT): X.XXX ms
CPU (NumPy): XX.XXX ms
Speedup: XXx

------------------------------------------------------------
VERIFICATION
------------------------------------------------------------
GPU vs CPU FFT magnitude: Test PASSED

Frequency Detection Accuracy:
     440 Hz: [OK]
     ...

Done

Note: Times and speedup vary by hardware.

Files

  • fftSignalAnalysis.py - Main sample using cuda.core and CuPy
  • README.md - This file
  • requirements.txt - Dependencies

See Also