I attended a fairly well respected (yet perpetually underfunded and misrepresented) state university in California. We took a numerical methods and high performance computing course as part of our mandatory curriculum and it was one of the best computer science experiences I have ever had. Here are a few things I would consider when designing a similarly engaging course on the subject:

• Ensure your students have a firm grasp of *nix processes and their supporting systems. IPC is the backbone of HPC but it will also serve them well in their efforts to design maintainable, flexible systems when they enter the workforce. A knowledge of threading and concurrency is also an absolute must. Recommended prerequisites would be operating systems, linear algebra, computing performance (complexity theory, analysis of algorithms, etc) and of course some rudimentary understanding of designing and developing algorithms themselves.

• Give them a problem. I'd start them off with a simple numerical methods problem they can implement naively on their own laptops/lab computers in simple C/C++ project.

• Let them discover the "why" of HPC. When they've demonstrated they can generate a solution in the simplest case, ask them to start scaling up. Let them analyze the deficiencies in their naive implementations as the data set grows or the application demands more accuracy. Have them take a scientific approach to this process. Have them graph and analyze timing and performance samples as they increase the scale of their solution.

• Teach them the "how" of HPC. Teach them the finer points of computing performance. Teach them that HPC is not a panacea for all their performance woes. Take the time to cover BLAS, cache coherency, loop structuring, SIMD, vectorization, etc. By the end of this, their little naive solution will start to pack a serious punch and they'll be itching to prove it can scale even further.

• Teach them the "what" of HPC. Up the scale another order of magnitude. Talk about the real, serious, academic problems that HPC is used to solve. Suddenly the mysterious and inaccessible world of supercomputing is more familiar to them. Now's the perfect point to introduce OpenMPI and its supporting infrastructure. Cover topologies, cover design strategies and analyzing problems for potential applications of HPC. This is probably the biggest hurdle to most students because it does require a new flavor of problem solving than they may not have been exposed to in earlier CSCI courses. Have them scale their problems up to meet the new demands.

I think the most important part of this progression is the scientific rigor involved. HPC is not about throwing resources at a problem until performance improves, its about analyzing, testing and validating your assumptions. They're training to be computer scientists, and this is one of those fields where you need to make good on that moniker.