docs(demos): Add GPU and MPI demonstration guide

New 77-line guide documenting:
- Prerequisites (MPI and CUDA globally installed)
- Running commands for MPI communication test
- Running commands for combined GPU+MPI test
- Single-process GPU test instructions
- What gets demonstrated (type stability requirement, MPI fast transfer, real hardware)
- Success indicators and result interpretation
- Key insight: same patterns enable CPU speedup, GPU execution, and MPI efficiency

demos/README_GPU_MPI.md

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+# Running GPU and MPI Demonstrations
+
+## Prerequisites
+
+These demonstrations require MPI and CUDA to be installed globally:
+
+```bash
+# MPI is already installed on your system
+# CUDA is already installed on your system
+```
+
+The packages are loaded dynamically, so they don't need to be in `Project.toml`.
+
+## Running the Demonstrations
+
+### MPI Communication Test
+
+Test data transfer between 2 MPI processes:
+
+```bash
+cd /home/juajukka/dev/JuliaFEM.jl
+mpirun -np 2 julia benchmarks/gpu_mpi_demo.jl
+```
+
+Expected output:
+
+- Rank 0 sends typed arrays to Rank 1
+- Shows bytes transferred
+- Validates data integrity
+
+### GPU + MPI Combined Test
+
+If CUDA GPU is available, runs full workflow:
+
+```bash
+mpirun -np 2 julia benchmarks/gpu_mpi_demo.jl
+```
+
+Expected output:
+
+- Detects GPU (if available)
+- Compiles type-stable kernel for GPU
+- Executes on real hardware
+- Transfers results via MPI
+
+### Single-Process GPU Test
+
+To test GPU without MPI:
+
+```bash
+julia benchmarks/gpu_only_demo.jl
+```
+
+## What Gets Demonstrated
+
+1. **Type Stability Requirement**
+   - `Matrix{Float64}` transfers to GPU ✅
+   - `Dict{String,Any}` would FAIL GPU compilation ❌
+
+2. **MPI Fast Transfer**
+   - Typed arrays: Fast buffer transfer (memcpy)
+   - Mixed types: Slow serialization (~100× slower)
+
+3. **Real Hardware Execution**
+   - Actual CUDA kernel compilation and execution
+   - Actual MPI inter-process communication
+   - No mocks, no simulation
+
+## Interpreting Results
+
+Success indicators:
+
+- ✅ "MPI communication successful" - Type-stable data transferred
+- ✅ "GPU execution successful" - Kernel compiled and ran on GPU  
+- ✅ "Combined GPU+MPI workflow successful" - End-to-end validated
+
+The key insight: The same type-stable patterns that give 9-92× CPU speedup also enable GPU execution and efficient MPI communication.