CS371p Fall 2020 Week 3: Abu-Zayd Abdullah
- What did you do this past week?
This past week I worked on cleaning up my Collatz solution and worked on the first lab for Network Security and Privacy. Having taken classes with Dr. Downing before this first lab did not require much extra work which was nice.
2. What’s in your way?
Balancing time between classes and doing personal projects is somewhat in my way. Other than that I have my lab for my aforementioned CS class that I am still working on.
3. What will you do next week?
Next week I will work on my other lab as well as attend lectures and hopefully learn about the second project for this class. I will also see about trying to squeeze in some time to work on LeetCode and my personal projects.
4. What was your experience of Collatz, the starter code, the makefile, its optimizations, and exceptions?
Nothing new, having taken both of Dr. Downing’s other classes before none of these were new to me though the refresher was nice. I do consider Collatz to be an interesting problem and this project does help to acclimate you to all the tools that will be used in the course.
5. What made you happy this week?
Me along with a friend managed to write a faster more updated version of a project that we initially wrote a few years ago which was pretty fun. Other than that talking with some friends I had not seen in a while was also great. I also finally had some time to watch a conference talk that I had been wanting to watch for a while.
6. What’s your pick-of-the-week or tip-of-the-week?
A project that I have enjoyed using recently is Numba which is an open-source JIT compiler that translates a subset of Python and NumPy code into efficient machine code. For performance oriented applications that also want to retain the quick development times that Python offers, this is a very useful tool. It is quite a impressive tool that has the ability to convert many Python programs into machine code using LLVM, an industry standard compiler library. I had the opportunity to use this at a past internship and the performance benefits are very pronounced with 500x improvement on CPU workloads and a almost 7300x improvement when parallelizing the application in question on a GPU. So definitely a tool to check out.
