Guilherme Bodin

SnoopCompile has a feature of timing the time spent in LLVM to optimize Julia code. This is a talk sharing my experiences using the macro snoopl to debug the time spent optimizing each function in LLVM.

In this talk, I would present my current workflow for debugging the time spent in LLVM optimizing functions and share my experience of using SnoopCompile to understand where are the problems of a large code base to perform faster Time To First X (TTFX).

Pinning Julia Threads to CPU-Cores with ThreadPinning.jl

32-141

Debugging time spent in LLVM with SnoopCompile

I would like to share with the JuMP community some of my experience building stochastic programming models in production, this talk will discuss design patterns used for an LNGC logistics problem developed in an R&D project.

In this talk, I will go through useful first principles on how to create maintainable stochastic programming JuMP applications by discussing different design patterns that make it easier to maintain a pipeline of building, modifying, solving, and retrieving solutions of JuMP models in an orderly manner. The design patterns go from how to structure the code directory to ways of separating code into functions of the complete stochastic programming pipeline. Everything will be discussed with an LNGC logistics problem as background.

Guilherme Bodin

Talks:

Debugging time spent in LLVM with SnoopCompile

Stochastic programming application for LNGC logistics

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