<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: saqibkhan1992</title><link>https://news.ycombinator.com/user?id=saqibkhan1992</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Thu, 20 Aug 2026 18:28:59 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=saqibkhan1992" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[Show HN: PantheonGPU – GPU health testing and AI workload benchmarking]]></title><description><![CDATA[
<p>Hi HN, I built PantheonGPU because I wanted a better way to answer a simple question: is this GPU actually healthy and performing the way it should?<p>A GPU can show normal temperatures and utilization and still be underperforming, unstable under certain workloads, or have memory, PCIe, or configuration issues.<p>PantheonGPU actively tests the GPU instead of only monitoring telemetry. It currently includes 45+ tests covering compute, tensor workloads, memory, cache, PCIe, thermals, stability, and AI/LLM inference.<p>It supports both NVIDIA CUDA and AMD ROCm.<p>I’m also exploring a larger use case: running Pantheon across GPU fleets to identify individual GPUs that behave differently from the rest of a server or cluster.<p>I’d especially appreciate feedback from people running AI infrastructure, multi-GPU systems, local LLMs, or GPU clouds.</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49350637">https://news.ycombinator.com/item?id=49350637</a></p>
<p>Points: 13</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 18 Aug 2026 18:47:51 +0000</pubDate><link>https://pantheongpu.com/</link><dc:creator>saqibkhan1992</dc:creator><comments>https://news.ycombinator.com/item?id=49350637</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49350637</guid></item></channel></rss>