Lib.rs

GPU Foundations: device array abstraction and CPU-backed baseline ops.

scir-gpu

Overview

• GPU foundations for SciR. Provides a minimal DeviceArray<T> abstraction, CPU baselines, and optional CUDA paths behind the cuda feature.

Features

• cuda: enables CUDA Driver API usage with embedded PTX kernels for f32 elementwise add/mul and batched FIR.

Requirements (CUDA)

• NVIDIA GPU with recent driver installed (libcuda present on host).
• On Linux, ensure libcuda.so is visible to the container or process; on Windows, nvcuda.dll is required.

Quick start

• CPU tests: cargo test -p scir-gpu
• CUDA tests: cargo test -p scir-gpu --features cuda

APIs

• DeviceArray<T>: shaped arrays with device and dtype. CPU-backed storage today.
• Elementwise: add_scalar_auto, mul_scalar_auto, add_auto (f32) dispatch to CUDA when available.
• FIR: fir1d_batched_f32_auto(x, taps, device) chooses CUDA or CPU and falls back to CPU if CUDA is unavailable.