The Jacobi iterative method is used to find approximate numerical solutions for systems of linear equations of the form Ax = b in numerical linear algebra, which is diagonally dominant. The algorithm starts with an initial estimate for x and iteratively updates it until convergence. The Jacobi method is guaranteed to converge if matrix A is diagonally dominant.
This document covers two approaches for CUDA to SYCL migration:
- The first approach is manual migration by analyzing CUDA source and replacing all CUDA-specific calls with equivalent SYCL calls. This approach helps a CUDA developer to understand SYCL programming. Once the migration is complete, we do performance analysis using VTuneTM Profiler and Intel® Advisor Roofline to understand the performance bottlenecks. We then look at optimizing the code for performance.
- The second approach is using Intel® oneAPI Data Parallel C++ Compatibility Tool (DPCT) to automatically migrate CUDA source to SYCL source. The tool migrates 80–90 percent of the code and generates a warning for the rest, which has to be manually migrated to SYCL. We look at DPCT generated warnings and learn how to migrate the code that was not migrated by the DPCT. This approach helps to accelerate the migration of CUDA source to SYCL and has proven especially helpful for large code bases.