GPU implementation of sparse equality constraint Jacobian

[pelesh]

Merge request type

• New feature
• Resolves bug
• Documentation
• Other

Relates to

• OPFLOW
• SOPFLOW
• SCOPFLOW
• TCOPFLOW
• CMake build system
• Spack configuration
• Manual
• Web docs
• Other

This MR updates

• Header files
• Source code
• CMake build system
• Spack configuration
• Web docs
• Manual
• Other

Summary

Merging branch by @kswirydo rebased to "OLCF" branch.

Port equality constraint Jacobian from PETSc to RAJA GPU kernels

Replace the PETSc-based equality constraint Jacobian computation in the
PBPOLRAJAHIOPSPARSE model with direct GPU kernels using RAJA, eliminating
the D2H-compute-H2D round trip. The sparsity pattern is now computed on
the host during setup and the values are computed entirely on device.

Key changes:
- Add ComputeEqJacValuesGPU_PBPOLRAJAHIOPSPARSE in new gpu.cpp/hpp files
- Add device arrays for flat-array indices (bus eqjacsp_selfidx, line
  eqjacsp_idx/eqjacsp_diag_idx/isdcline, gen xpdevidx/xpsetidx)
- Fix nnz counting bugs (missing gen/load entries, off-by-one in line
  loop) and populate flat-array indices during model setup
- Replace PETSc MatGetRow extraction in sparsity and values phases
- Handle parallel lines by sharing off-diagonal positions with atomicAdd
- Use pre-computed nnz in get_sparse_blocks_info instead of PETSc query
- Add correctness test (test_eqjac_compare) and performance benchmark
  (test_eqjac_perf)

Made-with: Cursor

This PR breaks HiOp MDS tests with RAJA! Need to investigate before merging to develop.

[pelesh]

Close in favor of #48