Accelerating Signal Processing using cuSignal

Signal processing is everywhere — from your phone calls and music streaming to radar systems and autonomous vehicles. But here’s the catch: 👉 Traditional Python signal processing (using SciPy) runs on CPU 👉 Real-world applications demand real-time performance That’s where cuSignal comes in. ⚡ What is cuSignal? cuSignal is a GPU-accelerated signal processing library built on top of: CuPy (GPU version of NumPy) Numba CUDA kernels Inspired by SciPy Signal API 💡 In simple terms: cuSignal lets you run your existing SciPy signal workflows on a GPU with minimal changes. 🧠 Why cuSignal Matters Signal processing workloads often involve: FFTs (Fast Fourier Transforms) Filtering Convolution Spectral analysis These are highly parallel operations , which GPUs excel at. Benefits: ⚡ Massive speedups (especially for large signals) 🔁 Minimal code changes from SciPy 🔗 Seamless integration with GPU ML frameworks like PyTorch 🏗️ Installation (Quick Setup) Currently, cuSignal is usually installed from sour