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Add full CS6969 link catalog via Codex
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‎index.html‎

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@@ -24,6 +24,7 @@ <h1>CS6969: Fast and Correct GPU Code</h1>
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<a href="#syllabus">Syllabus Snapshot</a>
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<a href="#projects">Projects</a>
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<a href="#resources">Resources</a>
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<a href="links.html">Full Links</a>
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</nav>
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<main>
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archived course materials and the semester documents in the repository.
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This homepage is meant to provide the compact public-facing summary.
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</p>
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<p>
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A consolidated catalog of the public URLs embedded throughout the main
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syllabus document and its side tabs is available here:
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<a href="links.html">Full Link Catalog</a>.
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</p>
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<div class="catalog-grid">
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<article class="catalog-card">
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<h3>Software Tools</h3>

‎links.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<meta name="description" content="Public link catalog extracted from the CS6969 syllabus and side-tab materials.">
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<title>CS6969 Link Catalog</title>
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<link rel="stylesheet" href="css/style.css">
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</head>
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<body>
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<header class="hero">
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<div class="hero-inner">
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<p class="eyebrow">CS6969 Resource Index</p>
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<h1>Full Link Catalog</h1>
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<p class="lede">
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Public URLs gathered from the main syllabus document and its side tabs,
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organized so students can browse software, papers, tutorials, slides,
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and project references more directly.
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</p>
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</div>
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</header>
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<nav class="topnav">
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<a href="index.html">Home</a>
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<a href="#course">Course Docs</a>
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<a href="#slides">Slides</a>
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<a href="#software">Software</a>
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<a href="#papers">Papers</a>
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<a href="#aws">AWS / Trainium</a>
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<a href="#systems">CHPC / Tools</a>
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</nav>
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<main>
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<section class="panel alt">
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<h2>About This Catalog</h2>
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<p>
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This page collects the public links embedded throughout the shared
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course planning material. It intentionally excludes a few non-public or
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unsafe entries, such as localhost-only URLs, one-time tokenized raw
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links, and machine-local pseudo-links that are not meaningful on a
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public course website.
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</p>
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</section>
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<section id="course" class="panel alt">
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<h2>Course Documents and Administration</h2>
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<ul>
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<li><a href="https://docs.google.com/document/d/10IxljmaHBsQD4aQsfeQ6ge0RgAawlupg5fAK2zCCI6Y/edit">Main syllabus Google Doc</a></li>
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<li><a href="https://class-schedule.app.utah.edu/main/1264/class_list.html?subject=CS">University of Utah class schedule</a></li>
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<li><a href="https://registrar.utah.edu/academic-calendars/spring2026.php">Spring 2026 academic calendar</a></li>
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<li><a href="mailto:cs6969@googlegroups.com">Class Google Group email</a></li>
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<li><a href="http://cs.utah.edu">School of Computing</a></li>
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<li><a href="https://dblp.org/pid/192/0371.html">Professor Sreepathi Pai on DBLP</a></li>
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<li><a href="https://soarlab.org/team/baranowski/">Mark Baranowski profile</a></li>
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</ul>
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</section>
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<section id="slides" class="panel alt">
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<h2>Slides, Notes, and Shared Class Documents</h2>
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<ul>
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<li><a href="https://docs.google.com/document/d/1hh-4Mn0vLGb3wZqg_fAu4COCmP2Hez7fUV8VY0CQpGs/edit?usp=sharing">Course organization notes</a></li>
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<li><a href="https://docs.google.com/presentation/d/1-KQhZabAgIDfrjPUgkTy4F6k2BqGpFiPdeS4oC_BKsw/edit?usp=sharing">Ganesh introductory slides</a></li>
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<li><a href="https://cs.rochester.edu/~sree/courses/cs6969-spring-2026/sree-intro.pdf">Sree intro slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1wLwiYiBSj3b4UrlhirfCdA2O1dPMqRIJh1LMdygTYuo/edit?usp=sharing">Number systems and tools slides</a></li>
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<li><a href="https://cs.rochester.edu/~sree/courses/cs6969-spring-2026/sree-perf-model.pdf">Performance model slides</a></li>
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<li><a href="https://cs.rochester.edu/~sree/courses/cs6969-spring-2026/sree-gpu-performance.pdf">GPU performance slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1mijmFYeSxJ5pfZKFdObCJYOC4lZWRzosEBBJF5XHgtM/edit?usp=sharing">GPU execution and schedule slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1C6vt0McbS2if2_AJoVdhWAzqrTK6owV8I71zlvUIOcE/edit?usp=sharing">AWS training slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1OVkwX4hO3V6tqrvNE9VwxiHOSabSzhxauVZp6ombeqU/edit?usp=sharing">Neuron architecture slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1usOJAgZCNI3hfuqcj6FZGrzEPrbEfTliG0mRRDcEEfs/edit?usp=sharing">Project and discussion slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1T9MSmJenR4EYb1L_14bUoOJWw-zd2CNq/edit?usp=sharing&ouid=111495655245157297413&rtpof=true&sd=true">Student or guest presentation deck</a></li>
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<li><a href="https://docs.google.com/presentation/d/1bYp46_MeOXH2d4MLdi26QyK8J3T8uYkIVsy7DJmx_Aw/edit?usp=sharing">MLIR / MLIR-AIR slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/13Wm5mQldICWj227BsHivin1ZhueXy4UJKfQorlbQ4KY/edit?usp=sharing">Faial / GKLEE slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1HtwRKhrrR_KWUkXmLafSuZEibsBGaiweGKG5agN1MQQ/edit?slide=id.g39d208624b6_0_943#slide=id.g39d208624b6_0_943">NVBit and barrier instrumentation slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/1pFQFBpJLGdtykpkOqhHX3gMY3YT7BSe107N7Np8Nkkw/edit?usp=sharing">SLEEK / later-semester slides</a></li>
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<li><a href="https://docs.google.com/presentation/d/19PnhI6rXAj9u4xkFHxK2075Zi_yGHFiRlnmneCUE7ow/edit?usp=sharing">Transform dialect / late-semester slides</a></li>
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<li><a href="https://drive.google.com/file/d/1s_U_C0-a3IPqwqosmPp-EyVOo0mR033I/view?usp=drive_link">Hoare logic supplemental file</a></li>
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<li><a href="https://drive.google.com/file/d/1GEJSDhAD597nMmb1t7WIlmR71VmgPez3/view?usp=sharing">AWS or profiling supplemental video/file</a></li>
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<li><a href="https://drive.google.com/file/d/1GEJSDhAD597nMmb1t7WIlmR71VmgPez3/view?usp=drive_link">AWS or profiling supplemental file mirror</a></li>
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<li><a href="https://drive.google.com/file/d/1jVM5Bu1RYEB2E9DlO_JojVinG7bPADWL/view?usp=drive_link">Additional AWS training video/file</a></li>
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<li><a href="https://docs.google.com/document/d/1udXciT93VtBP8rbrGBt8AcQoacZ5dxR6QHEqGaqBgfw/edit?usp=sharing">Software pipelining notes</a></li>
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<li><a href="https://www.overleaf.com/read/pcfjvhpzghpt#9ec326">Assignment Overleaf workspace</a></li>
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<li><a href="https://www.overleaf.com/read/kfzrpddjsdpn#6b6082">Asg-3 Overleaf workspace</a></li>
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<li><a href="https://www.overleaf.com/read/wxrsxmdttcgw#da21ab">AWS/reporting Overleaf workspace</a></li>
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</ul>
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</section>
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<section id="software" class="panel alt">
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<h2>Software, Repositories, and Tooling</h2>
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<ul>
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<li><a href="https://github.com/parfloat/parfloat-class">Course software repository</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/tree/main/TILUS">Tilus course checkout</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/tree/main/AIR2CUDA">AIR2CUDA course checkout</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/tree/main/MLIRXformTut">MLIR transform tutorial checkout</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/tree/gg_nixnan/barrier_nvbit/nvbit_release/tools/nixnan">Barrier NVBit tool checkout</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/blob/gg_nixnan/barrier_nvbit/docs/barrier_test_execution.pdf">Barrier NVBit execution notes</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/tree/gg_nixnan/nixnan/test/lu_solver/demo2">Nixnan LU demo</a></li>
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<li><a href="https://github.com/parfloat/parfloat-class/blob/gg_nixnan/nixnan/test/histogram/Results-3-3-higher-condnum.md">Nixnan histogram results</a></li>
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<li><a href="https://github.com/apache/tvm-ffi?tab=readme-ov-file">TVM FFI repository</a></li>
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<li><a href="https://tvm.apache.org/ffi/">TVM FFI documentation</a></li>
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<li><a href="https://github.com/eunomia-bpf/nvbit-tutorial/tree/main/tools/instr_count#what-are-predicates">NVBit instrumentation tutorial</a></li>
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<li><a href="https://github.com/burtscher/SLEEK/">SLEEK repository</a></li>
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<li><a href="https://github.com/AMD-AGI/GEAK-agent">GEAK repository</a></li>
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<li><a href="https://github.com/NVIDIA/TileGym">TileGym repository</a></li>
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<li><a href="https://github.com/rasbt">Sebastian Raschka repositories</a></li>
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<li><a href="https://github.com/aws-neuron/nki-samples">AWS Neuron NKI samples</a></li>
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<li><a href="https://github.com/aws-neuron/nki-samples/blob/main/src/nki_samples/tutorials/attention_fwd_performance/attention_kernels.py">NKI attention kernels source</a></li>
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<li><a href="https://github.com/stanford-cs149/asst4-trainium2">Stanford CS149 Trainium-2 assignment</a></li>
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<li><a href="https://github.com/keram88/aws-101-for-tranium?tab=readme-ov-file#5-automating-login">AWS Trainium starter guide</a></li>
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<li><a href="https://colab.research.google.com/github/sdiehl/gpu-offload/blob/main/Minimal.ipynb#scrollTo=XMQS0HOhCwvj">Stephen Diehl GPU offload notebook</a></li>
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<li><a href="https://stanford-cs336.github.io/spring2025/">Stanford CS336 LLM material</a></li>
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</ul>
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</section>
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<section id="papers" class="panel alt">
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<h2>Papers and Reading Links</h2>
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<ul>
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<li><a href="https://dl.acm.org/doi/10.1145/1882291.1882320">Scalable SMT-based verification of GPU kernel functions</a></li>
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<li><a href="https://ieeexplore.ieee.org/document/10289219">Facile: Fast, Accurate, and Interpretable Basic-Block Throughput Prediction</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/3524059.3532396">uiCA throughput prediction paper</a></li>
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<li><a href="https://cogumbreiro.github.io/assets/faial-popl26.pdf">Faial modular static cost analysis PDF</a></li>
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<li><a href="https://cogumbreiro.github.io/assets/faial-fmsd23.pdf">Memory Access Protocols / Faial-related paper PDF</a></li>
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<li><a href="https://arxiv.org/pdf/2504.12984">Tilus paper PDF</a></li>
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<li><a href="https://arxiv.org/abs/2509.21039">Mojo in HPC paper</a></li>
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<li><a href="https://graphics.pixar.com/library/RenderManXPU/">RenderMan XPU paper/page</a></li>
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<li><a href="https://arxiv.org/abs/2512.04226">tritonBLAS paper</a></li>
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<li><a href="https://arxiv.org/pdf/2511.13940">ParallelKittens paper</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/3001834">Hoare Logic of GPU Programs</a></li>
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<li><a href="https://arxiv.org/pdf/1903.07486">LLVM/IR or GPU optimization reading</a></li>
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<li><a href="https://openreview.net/pdf?id=0fJfVOSUra">OpenReview paper linked in syllabus</a></li>
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<li><a href="https://arxiv.org/abs/2511.08083">Recent paper linked in syllabus</a></li>
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<li><a href="https://arxiv.org/pdf/2002.11054">Additional accelerator/compiler reading</a></li>
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<li><a href="https://arxiv.org/abs/2510.14871">From Loop Nests to Silicon: Mapping AI Workloads onto AMD NPUs with MLIR-AIR</a></li>
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<li><a href="https://dl.acm.org/doi/epdf/10.1145/3318464.3380595">MLIR paper</a></li>
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<li><a href="https://dl.acm.org/doi/pdf/10.1145/2145816.2145844">GKLEE paper PDF</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/3352460.3358307">Another correctness/performance paper linked in syllabus</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/103162.103163">Goldberg floating-point classic</a></li>
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<li><a href="https://dl.acm.org/doi/pdf/10.1145/3736112.3736144">Recent linked paper PDF</a></li>
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<li><a href="https://userweb.cs.txstate.edu/~burtscher/papers/ipdps26.pdf">SLEEK IPDPS 2026 paper</a></li>
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<li><a href="https://llvm.org/devmtg/2025-10/slides/quick_talks/baskaran_slama.pdf">LLVM developer meeting slides</a></li>
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<li><a href="https://arxiv.org/pdf/2602.19762">Recent arXiv paper linked in syllabus</a></li>
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<li><a href="https://research.nvidia.com/publication/2026-03_hunting-cuda-bugs-scale-cufuzz">CuFuzz NVIDIA research page</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/3696443.3708922">Transform dialect or related compiler paper</a></li>
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<li><a href="https://arxiv.org/html/2504.12984v3">Tilus paper HTML view</a></li>
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<li><a href="https://arxiv.org/pdf/2511.12638">Equivalence Checking of GPU Kernels</a></li>
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<li><a href="https://arxiv.org/abs/2507.23194">GEAK paper</a></li>
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<li><a href="https://arxiv.org/abs/2511.12294">ProofWright paper</a></li>
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<li><a href="https://arxiv.org/abs/2502.10517">KernelBench paper</a></li>
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<li><a href="https://drops.dagstuhl.de/storage/00lipics/lipics-vol263-ecoop2023/LIPIcs.ECOOP.2023.13/LIPIcs.ECOOP.2023.13.pdf">Dynamic determinacy race detection paper PDF</a></li>
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<li><a href="https://www.arxiv.org/abs/2512.18134">Optimal software pipelining and warp specialization for tensor core GPUs</a></li>
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<li><a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=476167">Aiken 1995 software pipelining paper</a></li>
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<li><a href="https://vsl.cis.udel.edu/trac/civl/wiki">CIVL model checker</a></li>
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<li><a href="https://doi.org/10.1145/2076450.2076465">You don't know jack about shared variables or memory models</a></li>
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<li><a href="https://doi.org/10.1145/1543135.1542490">FastTrack race detection</a></li>
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<li><a href="https://doi.org/10.1145/2398857.2384625">GPUVerify paper</a></li>
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<li><a href="https://vercors.ewi.utwente.nl/">Vercors tool</a></li>
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<li><a href="https://ris.utwente.nl/ws/portalfiles/portal/24315485/Saeed_Darabi.pdf">Saeed Darabi thesis</a></li>
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<li><a href="https://dl.acm.org/doi/10.5555/3433701.3433768">Scalable yet rigorous floating-point error analysis</a></li>
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<li><a href="https://colab.research.google.com/drive/1W_FoAnQgYsmiQFlLEN_Pc3PwXl2NOhKB?usp=sharing">SMT Colab notebook</a></li>
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<li><a href="http://fpanalysistools.org">FP analysis tools</a></li>
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<li><a href="https://herbie.uwplse.org/">Herbie floating-point rewriting</a></li>
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<li><a href="https://vowi.fsinf.at/images/8/84/TU_Wien-GPU_Architectures_and_Programming_VU_(Bartocci)_-_GPU_Computing_Gems_Emerald_Edition.pdf">GPU Computing Gems</a></li>
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<li><a href="https://arxiv.org/abs/2503.17893">Recent performance-model paper</a></li>
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<li><a href="https://dl.acm.org/doi/10.1145/3725798.3725801">Shared-memory atomic bottlenecks paper DOI</a></li>
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<li><a href="https://www.sciencedirect.com/science/article/pii/S0743731522002295?dgcid=SSRN_redirect_SD&ssrnid=4059952">Analytical performance models for GPUs</a></li>
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</ul>
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</section>
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<section id="aws" class="panel alt">
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<h2>AWS Trainium, Neuron, and Profiling Links</h2>
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<ul>
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<li><a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/tools/neuron-explorer/how-to-profile-workload.html">Neuron Explorer profiling guide</a></li>
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<li><a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/tools/neuron-explorer/get-started.html#launch-the-api-and-ui-spa-servers">Neuron Explorer get-started guide</a></li>
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<li><a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/nki/deep-dives/use-neuron-profile.html">Profile a NKI kernel</a></li>
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<li><a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/nki/api/nki.isa.html#id1">NKI ISA documentation</a></li>
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<li><a href="https://awsdocs-neuron.readthedocs-hosted.com/en/v2.26.1/nki/tutorials/matrix_multiplication.html">NKI matrix multiplication tutorial</a></li>
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<li><a href="https://github.com/aws-neuron/nki-samples/tree/main/src/nki_samples/tutorials/attention_fwd_performance">NKI attention forward performance tutorial</a></li>
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<li><a href="https://utah.zoom.us/rec/share/yG3LRDlyn7ujehS_wbYnP8mFf4nUjFsDMUrChGuZBhY0JLNF4bhZA1hgk-80jQtM.1ILNdU0UfNRiiiY4?startTime=1770060311000">AWS / Trainium recorded session</a></li>
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</ul>
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</section>
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<section id="systems" class="panel alt">
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<h2>CHPC, Profiling, and System Access</h2>
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<ul>
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<li><a href="https://www.chpc.utah.edu/documentation/software/slurm-gpus.php">CHPC GPU usage guide</a></li>
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<li><a href="http://granite.chpc.utah.edu">Granite CHPC host</a></li>
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<li><a href="http://notchpeak.chpc.utah.edu">Notchpeak CHPC host</a></li>
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<li><a href="https://developer.nvidia.com/nsight-systems">Nsight Systems download page</a></li>
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</ul>
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</section>
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<section class="panel alt">
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<h2>Video and Media Links</h2>
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<ul>
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<li><a href="https://youtu.be/Uno_XhtkT5E?si=N4m2nYUUykKaRLIH">Course-linked YouTube video</a></li>
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<li><a href="https://youtu.be/hkgWi0oN_L8?si=Cl_H2Se2AlYvKmqN">Additional linked YouTube video</a></li>
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<li><a href="https://graphics.pixar.com/library/RenderManXPU/">RenderMan XPU media/library page</a></li>
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</ul>
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</section>
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</main>
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<footer>
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<p><a href="index.html">Back to CS6969 homepage</a></p>
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</footer>
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</body>
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</html>

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