Chris Leary
Chris Leary is a software engineer whose AI work spans compilers and accelerator hardware. He co-authored a Tensor Processing Unit study and presented XLA's TensorFlow compiler work with Todd Wang in 2017. His 2018 JAX paper described a tracing compiler for Python and NumPy, and his later Google talks covered XLA, JAX and XLS hardware synthesis. As of October 2026, he is a Member of Technical Staff at OpenAI and presents its Jalapeño inference chip.
Timeline
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March 2017
XLA for TensorFlow
At the TensorFlow Developer Summit in 2017, he and Todd Wang explain how TensorFlow uses XLA, JIT and ahead-of-time compilation to reduce execution time.
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April 2017
A Tensor Processing Unit study
He co-authors a 2017 study that evaluates a datacenter Tensor Processing Unit for neural-network inference and compares it with server CPUs and GPUs.
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2018
JAX and high-level tracing
He co-authors a 2018 SysML paper that describes JAX as a tracing JIT compiler for Python and NumPy machine-learning programs, with XLA generating optimized accelerator code.
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March 2022
XLA, JAX and XLS
At Cornell's LATTE accelerator-design workshop in March 2022, he recounts a decade of development across XLA, JAX and XLS, with acceleration targets at data-center scale.
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October 2022
Formal methods in XLS
At ADAPTOR in October 2022, he gives a keynote on XLS, a high-level synthesis toolchain for hardware blocks, and discusses equivalence checking and floating-point verification.
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As of October 2026
OpenAI hardware presentation
He is a Member of Technical Staff at OpenAI and presents its Jalapeño inference chip at Hot Chips 2026.
Career
Most-cited works
Sources and credits
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