New 203-line GPU-only demonstration (simplified without MPI complexity):
Setup and validation (lines 1-52):
- Checks for CUDA availability, exits if not found
- Reports GPU model and memory
- Sets up problem: 10000 nodes, 1000 elements
- Type-stable data: nodes (Float64), connectivity (Int), E, ν
GPU kernel (lines 54-120):
- assemble_element_kernel! for CUDA
- Type-stable: Float64, Int32, CuDeviceMatrix/Vector
- No allocations in kernel
- Computes simplified assembly: K_local = E * (1-ν²)
Execution (lines 122-170):
- Transfers data to GPU (nodes, connectivity)
- Reports bytes transferred
- Launches kernel with thread blocks
- Transfers results back from GPU
Verification (lines 172-203):
- Compares computed vs expected values
- Reports success/failure
- Key achievements summary:
* Type-stable kernel compiled
* Fast GPU memory transfer (typed arrays)
* Zero allocations in kernel
- Why it matters: Dict-based storage CANNOT compile for GPU
- Conclusion: type stability required for modern HPC
Purpose: Simpler test than full MPI version, focuses on GPU capability
Run: julia demos/gpu_only_demo.jl (requires CUDA GPU)
Jukka Aho