cuda-samples/python/2_CoreConcepts/fftSignalAnalysis

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:

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

# Use with CuPy operations
cp.cuda.ExternalStream(int(stream.handle)).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.ExternalStream() - 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

pip install -r requirements.txt

How to Run

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: ✓
     ...

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

• cuda.core Documentation
• CuPy FFT Documentation
• cuFFT Documentation