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Performance Engineering on Hard Mode with Andrew Hunter

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Manage episode 386390932 series 2784495
Content provided by Jane Street. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jane Street or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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:

  continue reading

21 episodes

Artwork
iconShare
 
Manage episode 386390932 series 2784495
Content provided by Jane Street. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jane Street or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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:

  continue reading

21 episodes

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