5 Subjects Every Computer Science Student Should Learn

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I was fortunate this year to attend the Association for Computer Machinery’s SIGCSE (Special Interest Group on Computer Science Education) conference, where there was a good deal of conversation about what a modern computer science curriculum should include.

Technology changes quickly and it can be difficult for academic programs to keep pace. Still, if computer science students are to contribute meaningfully to the field in either industry or research jobs, it’s critical that they learn modern computing skills. Here are five subjects I think every higher education institution should teach their undergraduate computer science majors:

1. Parallel Programming

The single, standalone server with one CPU has gone the way of the dodo bird, displaced by the cloud, server farms and multithreaded parallel processors. Yet colleges and universities are still mainly teaching their undergraduates sequential programming—programs that execute instructions one after the other—as they have for decades.

Modern computing environments and massive data sets demand not just that we process multiple instructions simultaneously across multiple servers (distributed computing), but also that programs be written to process multiple instructions simultaneously on multicore chips within multiple servers and devices.

Too often, parallel programming is relegated to a single chapter in a textbook, easily skipped when time in the semester runs short. To prepare students for high-performance computing, big data, machine learning, blockchain and more, we must teach them to both think and program in parallel.

2. Green Programming

With the ubiquity of battery-driven computers, energy efficiency is more important than ever. The more we ask our smart devices to do, the more energy they need to do it and the more quickly they exhaust their batteries. The same is true for massive server clusters, where fires related to energy-consumption are not uncommon as we demand faster and faster processing of more and more data.

How you architect a software program directly affects how much energy is needed to execute the program, yet few undergraduate programs teach students about this relationship. In a fast-warming world, one in which we dream big dreams about all the ways artificial intelligence and high-performance computing will make our lives better, it is imperative that we write energy-optimized software. Students will not be able to do that if we don’t teach them how.

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