May 1 · 3 min read · Introduction The recent advancements in GPU technology have set new standards for performance, especially in the realm of artificial intelligence (AI). Nvidia's H200 GPU, boasting an impressive 282GB of VRAM, is a game-changer for developers focusing...
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Feb 17 · 7 min read · At Trainy, we work on infrastructure for managing GPU clusters, so we spend a lot of time thinking about this stuff. Last year we were working with a foundation model company to scale out and improve the efficiency of their LLM training. We went thro...
Join discussionSep 8, 2025 · 6 min read · LLM Coding assistant or LLM Chatbots has become a daily companion to programmers and CS students. Today, when learning something completely new, we often start by asking ChatGPT, Claude, or Perplexity. When encounter an unknown error, we let them exp...
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Jul 26, 2025 · 4 min read · When You Need Gang Scheduling Applications that require coordinated multi-pod execution: Distributed ML Training: Multi-GPU model training (PyTorch DDP, TensorFlow Distributed) High-Performance Computing: Weather simulation, molecular dynamics Par...
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Mar 21, 2025 · 8 min read · TL;DR: How Innovative GPU Memory Strategies Are Breaking the Memory Wall in Deep Learning The GPU memory wall arises from the widening gap between rapidly increasing GPU compute power and much slower
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Feb 27, 2025 · 15 min read · Sometimes listening is easier: Here Introduction to ONNX Runtime ONNX Runtime (ORT) is a cross-platform machine-learning model accelerator developed by Microsoft for high-performance model deployment. It serves as a unified engine that can execute m...
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Feb 7, 2025 · 7 min read · TL;DR — AI-Driven GPU Code Optimization Performance Gains: AI-optimized models can achieve up to 4.5x runtime performance improvements and significantly reduce memory footprint. Industry Impact: Applications span healthcare (faster diagnostics), fi...
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