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Clock synchronization, keeping all of the clocks on your network set to the “correct” time, sounds straightforward: our smartphones sure don’t seem to have trouble with it. Next, keep them all accurate to within 100 microseconds, and prove that you did -- now things start to get tricky. In this episode, Ron talks with Chris Perl, a systems engineer at Jane Street about the fundamental difficulty of solving this problem at scale and how we solved it. You can find the transcript for this podcast episode along with links to things we discussed at signalsandthreads.com.

It is said that good things come to those who wait. Jacques-Henri Jourdan demonstrated Statistically profiling memory in OCaml at the 2016 OCaml Workshop and experimental branches of it existed for OCaml 4.03–4.07 in opam. Parts of the work were merged in OCaml 4.10 and the final sections landed with 4.11. The compiler provides support in the form of a series of hooks in various parts of the runtime’s allocation and garbage collection routines. A few weeks ago, Jane Street released memtrace and Memtrace viewer and earlier this week blogged about its use. I thought I’d quickly share the experience of using it on native Windows.

A conversation with Laurent Mazare about how your choice of programming language interacts with the kind of work you do, and in particular about the tradeoffs between Python and OCaml when doing machine learning and data analysis. Ron and Laurent discuss the tradeoffs between working in a text editor and a Jupyter Notebook, the importance of visualization and interactivity, how tools and practices vary between language ecosystems, and how language features like borrow-checking in Rust and ref-counting in Swift and Python can make machine learning easier. You can find the transcript for this podcast episode along with links to things we discussed at signalsandthreads.com.

A conversation with Laurent Mazare about how your choice of programming language interacts with the kind of work you do, and in particular about the tradeoffs between Python and OCaml when doing machine learning and data analysis. Ron and Laurent discuss the tradeoffs between working in a text editor and a Jupyter Notebook, the importance of visualization and interactivity, how tools and practices vary between language ecosystems, and how language features like borrow-checking in Rust and ref-counting in Swift and Python can make machine learning easier. You can find the transcript for this podcast episode along with links to things we discussed at signalsandthreads.com.

Memory issues can be hard to track down. A function that onlyallocates a few small objects can cause a space leak if it’s calledoften enough and those object...

It’s a software engineer’s dream: A compiler that can take idiomatic high-level code and output maximally efficient instructions. Ron’s guest this week is Greta Yorsh, who has worked on just that problem in a career spanning both industry and academia. Ron and Greta talk about some of the tricks that compilers use to make our software faster, ranging from feedback-directed optimization and super-optimization to formal analysis. You can find the transcript for this episode along with links to things we discussed at signalsandthreads.com.