<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Chai on Robert Carson</title><link>https://robertcarson.org/tags/chai/</link><description>Recent content in Chai on Robert Carson</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Robert Carson</copyright><lastBuildDate>Tue, 15 Apr 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://robertcarson.org/tags/chai/index.xml" rel="self" type="application/rss+xml"/><item><title>SNLS: A Small Nonlinear Solver Library That Punches Above Its Weight</title><link>https://robertcarson.org/projects/snls/</link><pubDate>Tue, 15 Apr 2025 00:00:00 +0000</pubDate><guid>https://robertcarson.org/projects/snls/</guid><description>&lt;h2 class="relative group"&gt;Where It Started
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&lt;p&gt;SNLS predates both ExaCMech and ExaConstit. It was developed at LLNL specifically to solve the problem of running material model constitutive updates on the GPU, at a time when no existing nonlinear solver library was designed to do that. General-purpose solvers like MINPACK or PETSc are built for problems that live on the host. They carry significant overhead per call and are not structured for batched execution across millions of independent points simultaneously. In crystal plasticity specifically, every quadrature point in the mesh needs its own nonlinear solve to update stress and internal state at each time step, and those systems are dense, stiff, and need to run as fast as possible without any per-point failure being an option. That was the gap SNLS was built to fill.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://robertcarson.org/projects/snls/feature.png"/></item></channel></rss>