ferrotorch-gpu

CUDA GPU backend for ferrotorch.

What it provides

• GpuDevice -- CUDA device management and context handling
• Data transfer -- cpu_to_gpu, gpu_to_cpu, tensor_to_gpu, tensor_to_cpu, alloc_zeros
• GpuTensor -- GPU-resident tensor wrapper with cuda() and cuda_default() helpers
• CUDA buffer -- CudaBuffer for raw GPU memory, CudaAllocator for memory management
• BLAS -- gpu_matmul_f32, gpu_matmul_f64 via cuBLAS
• Convolution -- gpu_conv2d_f32
• Element-wise kernels -- gpu_add, gpu_sub, gpu_mul, gpu_neg, gpu_relu
• Memory guard -- MemoryGuard, MemoryWatchdog, MemoryStats, OomPolicy for GPU memory management and pressure monitoring

Feature flags

Quick start

use ferrotorch_gpu::{GpuDevice, cpu_to_gpu, gpu_to_cpu};

let device = GpuDevice::new(0)?;
let host_data = vec![1.0f32, 2.0, 3.0];
let gpu_buf = cpu_to_gpu(&host_data, &device)?;
let back = gpu_to_cpu(&gpu_buf, &device)?;
assert_eq!(back, host_data);

Part of ferrotorch

This crate is one component of the ferrotorch workspace. See the workspace README for full documentation.

License

MIT OR Apache-2.0