Signals and Threads

Sylvain Gugger is a former math teacher who fell into machine learning via a MOOC and became an expert in the low-level performance details of neural networks. He’s now on the ML infrastructure team at Jane Street, where he helps traders speed up their models. In this episode, Sylvain and Ron go deep on learning rate schedules; the subtle performance bugs PyTorch lets you write; how to keep a hungry GPU well-fed; and lots more, including the foremost importance of reproducibility in training runs. They also discuss some of the unique challenges of doing ML in the world of trading, like the unusual size and shape of market data and the need to do inference at shockingly low latencies.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• “Practical Deep Learning for Coders,” a FastAI MOOC by Jeremy Howard, and the book, of which Sylvain is a co-author.
• The Stanford DAWNBench competition that Sylvain participated in.
• HuggingFace, and the Accelerate library that Sylvain wrote there.
• Some of the languages/systems for expression ML models that were discussed: PyTorch, TensorFlow, Jax, Mojo, and Triton
• CUDA graphs and streams
• Hogwild concurrency

Liora Friedberg is a Production Engineer at Jane Street with a background in economics and computer science. In this episode, Liora and Ron discuss how production engineering blends high-stakes puzzle solving with thoughtful software engineering, as the people doing support build tools to make that support less necessary. They also discuss how Jane Street uses both tabletop simulation and hands-on exercises to train Production Engineers; what skills effective Production Engineers have in common; and how to create a culture where people aren’t blamed for making costly mistakes.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• More about production engineering at Jane Street, including how to apply.
• Notes on Site reliability engineering in the wider world.
• Alarm fatigue and desensitization.
• Jane Street’s 1950’s era serialization-format of choice,
• Some games that Streeters have used for training people to respond to incidents.

Erin Murphy is Jane Street’s first UX designer, and before that, she worked at NASA’s Jet Propulsion Laboratory building user interfaces for space missions. She’s also an illustrator with her own quarterly journal. In this episode, Erin and Ron discuss the challenge of doing user-centered design in an organization where experts are used to building tools for themselves. How do you bring a command-line interface to the web without making it worse for power users? They also discuss how beauty in design is more about utility than aesthetics; what Jane Street looks for in UX candidates; and how to help engineers discover what their users really want.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Erin’s website that shows off her work.
• Her quarterly journal of sketches and observations.
• An article about Erin’s design work with NASA JPL.
• A paper that among other things talks about the user study work that Erin did at JPL.
• Jane Street’s current UX job opening.

Andrew Hunter makes code really, really fast. Before joining Jane Street, he worked for seven years at Google on multithreaded architecture, and was a tech lead for tcmalloc, Google’s world-class scalable malloc implementation. In this episode, Andrew and Ron discuss how, paradoxically, it can be easier to optimize systems at hyperscale because of the impact that even miniscule changes can have. Finding performance wins in trading systems—which operate at a smaller scale, but which have bursty, low-latency workloads—is often trickier. Andrew explains how he approaches the problem, including his favorite profiling techniques and tools for visualizing traces; the unique challenges of optimizing OCaml versus C++; and when you should and shouldn’t care about nanoseconds. They also touch on the joys of musical theater, and how to pass an interview when you’re sleep-deprived.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• “Profiling a warehouse-scale computer”
• Magic-trace
• OODA loop

Peter Bogart-Johnson was one of Jane Street’s first program managers, and helped bring the art of PMing—where that “P” variously stands for “project,” “product,” or some blend of the two—to the company at large. He’s also a poet and the editor of a literary magazine. In this episode, Peter and Ron discuss the challenge of gaining trust as an outsider: how do you teach teams a new way of doing things while preserving what’s already working? The key, Peter says, is you listen; a good PM is an anthropologist. They also discuss how paying down technical debt isn’t something you do instead of serving customers; what Jane Street looks for in PM candidates; and how to help teams coordinate in times of great change.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• LIT Magazine (more recently here)
• How to be a PM that engineers don’t hate and How to be an engineer that PMs don’t hate

Richard Eisenberg is one of the core maintainers of Haskell. He recently joined Jane Street’s Tools and Compilers team, where he hacks on the OCaml compiler. He and Ron discuss the powerful language feature that got him into PL design in the first place—dependent types—and its role in a world where AIs can (somewhat) competently write your code for you. They also discuss the differences between Haskell and OCaml; the perils of trying to make a language that works for everybody; and how best a company like Jane Street can collaborate with the open source community.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Dependent types
• GHC
• Unboxed types in OCaml
• Language extensions in Haskell

Ella Ehrlich has been a developer at Jane Street for close to a decade. During much of that time, she’s worked on Gord, one of Jane Street’s oldest and most critical systems, which is responsible for normalizing and distributing the firm’s trading data. Ella and Ron talk about how to grow and modernize a legacy system without compromising uptime, why game developers are the “musicians of software,” and some of the work Jane Street has done to try to hire a more diverse set of software engineers.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• EG, The League of Legends team that Ella is a huge fan of.
• Apache Kafka, the message bus that Gord migrated to.
• Some of the various sources of symbology you have to deal with when normalizing trading data. (Really, there are too many sources to list here!)
• A list of Jane Street’s recruiting Programs and Events, including INSIGHT, which focuses on women, and IN FOCUS, which focuses on historically underrepresented ethnic or racial minorities.

Doug Patti is a developer in Jane Street’s Client-Facing Tech team, where he works on a system called Concord that undergirds Jane Street’s client offerings. In this episode, Doug and Ron discuss how Concord, which has state-machine replication as its core abstraction, helps Jane Street achieve the reliability, scalability, and speed that the client business demands. They’ll also discuss Doug’s involvement in building a successor system called Aria, which is designed to deliver those same benefits to a much wider audience.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Jane Street’s client-facing trading platforms
• A Signals and Threads episode on market data and multicast which discusses some of the history of state-machine replication in the markets.
• The FIX protocol
• UDP multicast
• Reliable multicast
• Kafka

Stephen Dolan works on Jane Street’s Tools and Compilers team where he focuses on the OCaml compiler. In this episode, Stephen and Ron take a trip down memory lane, discussing how to manage computer memory efficiently and safely. They consider trade-offs between reference counting and garbage collection, the surprising gains achieved by prefetching, and how new language features like local allocation and unboxed types could give OCaml users more control over their memory.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Stephen’s command-line JSON processor, jq
• Stephen’s Cambridge dissertation, “Algebraic Subtyping”, and a protoype implementation of mlsub, a language based on those ideas.
• A post from Stephen on how to benchmark different memory allocators.
• A Jane Street tech talk on “Unboxed Types for OCaml”, and an RFC in the OCaml RFC repo.
• A paper from Stephen and KC Sivaramakrishnan called “Bounding Data Races in Space and Time”, which is all about a new and better memory model for Multicore OCaml.
• Another paper describing the design of OCaml’s multicore GC.
• The Rust RFC for Higher-ranked trait bounds.

Anil Madhavapeddy is an academic, author, engineer, entrepreneur, and OCaml aficionado. In this episode, Anil and Ron consider the evolving role of operating systems, security on the internet, and the pending arrival (at last!) of OCaml 5.0. They also discuss using Raspberry Pis to fight climate change; the programming inspiration found in British pubs and on Moroccan beaches; and the time Anil went to a party, got drunk, and woke up with a job working on the Mars Polar Lander.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Ron, Anil, and Jason Hickey’s book, “Real World OCaml”
• Anil’s personal website and Google Scholar page
• The MirageOS library operating system
• Cambridge University’s OCaml Labs
• NASA’s Mars Polar Lander
• The Xen Project, home to the hypervisor
• The Tezos proof-of-stake blockchain
• The Coq Proof Assistant system

Ty Overby is a programmer in Jane Street’s web platform group where he works on Bonsai, our OCaml library for building interactive browser-based UI. In this episode, Ty and Ron consider the functional approach to building user interfaces. They also discuss Ty’s programming roots in Neopets, what development features they crave on the web, the unfairly maligned CSS, and why Excel is “arguably the greatest programming language ever developed.”

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• Jane Street’s Bonsai library
• The 3D design system OpenSCAD
• Matt Keeter’s libfive design tools
• Try .NET in-browser repl
• Jane Street’s Incr_dom library
• The Elm Architecture “pattern for architecting interactive programs”
• React JavaScript library
• The Houdini proposal
• Svelte UI toolkit

James Somers is Jane Street’s writer-in-residence, splitting his time between English and OCaml, and helping to push forward all sorts of efforts around knowledge-sharing at Jane Street. In this episode, James and Ron talk about the role of technical writing in an organization like Jane Street, and how engineering software relates to editing prose.

You can find the transcript for this episode  on our website.

Some links to topics that came up in the discussion:

• mdx, the modified Markdown format that supports executing OCaml code blocks
• More on the 4 types of technical writing that James references
• Donald Knuth’s original book on Literate Programming
• More on John McPhee’s use of KEDIT
• Peter Seibel’s Coders at Work
• David Goodsell’s The Machinery of Life
• Scott Huler’s Defining the Wind

Some of James’s writing on our tech blog

Signals & Threads is back, and we have a fun season of topics lined up, including: Building better abstractions for design and user interfaces, the role of writing in a technical organization, the approach that different languages take to memory management...and more. We hope you’ll join us. The first episode drops September 1st.

In this week's episode, the season 1 finale, Ron speaks with Jeanne, Matt, and Grace, three former tech interns at Jane Street who have returned as full-timers. They talk about the experience of being an intern at Jane Street, the types of projects that interns work on, and how they've found the transition to full-time work.

You can find the transcript for this episode along with links to things we discussed on our website.

Despite a steady trickle of newcomers, email still reigns supreme as the chief communication mechanism for the Information Age. At Jane Street, it’s just as critical as anywhere, but there’s one difference: the system at the heart of our email infrastructure is homegrown. This week, Ron talks to Dominick LoBraico, an engineer working on Jane Street’s technology infrastructure, about how and why we built Mailcore, an email server written and configured in OCaml. They delve into questions around how best to represent the configuration of a complex system, when you should build your own and when you shouldn’t, and the benefits of bringing a code-focused approach to solving systems problems.

You can find the transcript for this episode along with links to things we discussed on our website.

Equal parts science and art, programming language design is very much an unsolved problem. This week, Ron speaks with Leo White, from Jane Street's Tools & Compilers team, about cutting-edge language features, future work happening on OCaml, and Jane Street's relationship with the broader open-source community. The conversation covers everything from the paradox of language popularity, to advanced type system features like modular implicits and dependent types. Listen in, no programming languages PhD required!

You can find the transcript for this episode along with links to things we discussed on our website.

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 episode along with links to things we discussed on our website.

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 episode along with links to things we discussed on our website.

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 on our website.

Electronic exchanges like Nasdaq need to handle a staggering number of transactions every second. To keep up, they rely on two deceptively simple-sounding concepts: single-threaded programs and multicast networking. In this episode, Ron speaks with Brian Nigito, a 20-year industry veteran who helped build some of the earliest electronic exchanges, about the tradeoffs that led to the architecture we have today, and how modern exchanges use these straightforward building blocks to achieve blindingly fast performance at scale.

You can find the transcript for this episode along with links to things we discussed on our website.