# Hopper

Published articles for Hopper.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## NVIDIA Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure

DevFeed: [NVIDIA Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure](<https://devfeed.tech/articles/nvidia-exemplar-cloud-lessons-for-unlocking-full-performance-on-ai-infrastructure-6891.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/nvidia-exemplar-cloud-lessons-for-unlocking-full-performance-on-ai-infrastructure/>)

Author: Elizabeth Goodman

Published: 2026-07-30T16:00:00Z

Content type: tutorial

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [debugging](<https://devfeed.tech/topics/debugging.md>), [Processes](<https://devfeed.tech/topics/processes.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cloud-services](<https://devfeed.tech/tags/cloud-services.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [debugging](<https://devfeed.tech/tags/debugging.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [dgx-cloud](<https://devfeed.tech/tags/dgx-cloud.md>), [diagnostics](<https://devfeed.tech/tags/diagnostics.md>), [distributed-training](<https://devfeed.tech/tags/distributed-training.md>), [featured](<https://devfeed.tech/tags/featured.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gb300-nvl72](<https://devfeed.tech/tags/gb300-nvl72.md>), [grace-cpu](<https://devfeed.tech/tags/grace-cpu.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [infiniband](<https://devfeed.tech/tags/infiniband.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [kernel](<https://devfeed.tech/tags/kernel.md>), [linux](<https://devfeed.tech/tags/linux.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [training](<https://devfeed.tech/tags/training.md>)

### AI overview

A troubleshooting guide for closing AI-training throughput gaps between NVIDIA reference architectures and partner clusters. It covers configuration and installation issues across memory management, CPU power and NUMA placement, NCCL queue-pair concurrency, and hardware setup.

### Source excerpt

Two AI computing clusters built from identical NVIDIA H100, GB200 NVL72, or GB300 NVL72 systems can deliver materially different training throughput. We...

## An AI Engineer's Guide To Choosing GPUs

DevFeed: [An AI Engineer's Guide To Choosing GPUs](<https://devfeed.tech/articles/an-ai-engineer-s-guide-to-choosing-gpus-35011.md>)

Original publisher: [Read original article](<https://read.theaimerge.com/p/an-ai-engineers-guide-to-choosing>)

Author: Alex Razvant

Published: 2025-12-07T14:02:40Z

Content type: tutorial

Language: en

Sources: [Neural Bits](<https://devfeed.tech/sources/neural-bits.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Blackwell](<https://devfeed.tech/topics/blackwell.md>), [Hopper](<https://devfeed.tech/topics/hopper.md>), [lora](<https://devfeed.tech/topics/lora.md>), [NCCL](<https://devfeed.tech/topics/nccl.md>), [Kernel](<https://devfeed.tech/topics/kernel.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-engineer](<https://devfeed.tech/tags/ai-engineer.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [clusters](<https://devfeed.tech/tags/clusters.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [deep-dive](<https://devfeed.tech/tags/deep-dive.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llm](<https://devfeed.tech/tags/llm.md>), [ml](<https://devfeed.tech/tags/ml.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [pcie](<https://devfeed.tech/tags/pcie.md>), [software](<https://devfeed.tech/tags/software.md>), [technical](<https://devfeed.tech/tags/technical.md>)

### AI overview

A technical guide to choosing NVIDIA GPUs for AI workloads. It explains how GPU microarchitecture, memory subsystems, form factors, and interconnects affect capabilities, scaling, training, and inference, and compares consumer and data-center GPUs.

### Source excerpt

A deep dive on technical Hardware and Software details of NVIDIA GPUs for AI Workloads.

## Introducing Training Cluster as a Service - a new collaboration with NVIDIA

DevFeed: [Introducing Training Cluster as a Service - a new collaboration with NVIDIA](<https://devfeed.tech/articles/introducing-training-cluster-as-a-service-a-new-collaboration-with-nvidia-7373.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/nvidia-training-cluster>)

Author: Jeff Boudier; Arjuna; Simon Pagezy

Published: 2025-06-11T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [anthropic](<https://devfeed.tech/topics/anthropic.md>), [NVIDIA DGX](<https://devfeed.tech/topics/nvidia-dgx.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [GB200](<https://devfeed.tech/topics/gb200.md>), [Hopper](<https://devfeed.tech/topics/hopper.md>), [Monitoring](<https://devfeed.tech/topics/monitoring.md>)

Tags: [announcement](<https://devfeed.tech/tags/announcement.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [dgx-cloud](<https://devfeed.tech/tags/dgx-cloud.md>), [gb200](<https://devfeed.tech/tags/gb200.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [libraries](<https://devfeed.tech/tags/libraries.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partners](<https://devfeed.tech/tags/partners.md>), [partnerships](<https://devfeed.tech/tags/partnerships.md>), [training](<https://devfeed.tech/tags/training.md>)

### AI overview

Hugging Face and NVIDIA introduce Training Cluster as a Service, connecting organizations with GPU cluster capacity for AI model training. Organizations can request clusters sized for their needs and pay for the duration of training runs. The service combines NVIDIA Cloud Partners, NVIDIA DGX Cloud Lepton, and Hugging Face developer resources and open source libraries, with Hugging Face and NVIDIA coordinating procurement, pricing, provisioning, and setup.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Исследуем баг iOS с помощью Hopper

DevFeed: [Исследуем баг iOS с помощью Hopper](<https://devfeed.tech/articles/ios-hopper-23612.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/badoo/articles/504084/>)

Author: WisDooMer (Badoo)

Published: 2020-05-28T11:03:02Z

Content type: tutorial

Language: ru

Sources: [Badoo EN](<https://devfeed.tech/sources/badoo-en.md>), [Badoo RU](<https://devfeed.tech/sources/badoo-ru.md>)

Topics: [iOS](<https://devfeed.tech/topics/ios.md>), [Hopper](<https://devfeed.tech/topics/hopper.md>)

Tags: [apple](<https://devfeed.tech/tags/apple.md>), [badoo](<https://devfeed.tech/tags/badoo.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [ios](<https://devfeed.tech/tags/ios.md>), [ios-92ecabba3495](<https://devfeed.tech/tags/ios-92ecabba3495.md>), [ios-development](<https://devfeed.tech/tags/ios-development.md>), [tag-8ecb3d630e31](<https://devfeed.tech/tags/tag-8ecb3d630e31.md>)

### AI overview

An iOS developer from Badoo investigates why telephone-number predictive keyboard suggestions disappeared in iOS 13. The article traces the issue to a keyboard implementation refactor and demonstrates restoring the suggestions in a test project using method swizzling.

### Source excerpt

Привет! Меня зовут Александр Никишин, я занимаюсь разработкой iOS-приложений в компании Badoo. В статье я расскажу о том, как мы исследовали баг в UIKit, который Apple не хотела исправлять на протяжении полугода. Всё началось в августе 2019 года с первых бета-версий iOS 13. Тогда мы впервые столкнулись с проблемой. В приложениях Badoo и Bumble мы постоянно работаем над улучшением интерфейсов и, например, стараемся максимально оптимизировать нудный и не любимый пользователями процесс регистрации. Системные предиктивные подсказки над клавиатурой -- отличный способ сокращения количества кликов пользователя при вводе данных. Однако в новой версии iOS мы с удивлением обнаружили, что подсказки при вводе номера телефона пропали. Читать дальше ->

## Looking Back on the Grace Hopper Celebration

DevFeed: [Looking Back on the Grace Hopper Celebration](<https://devfeed.tech/articles/looking-back-on-the-grace-hopper-celebration-15753.md>)

Original publisher: [Read original article](<https://developer.squareup.com/blog/looking-back-on-the-grace-hopper-celebration>)

Author: Square Engineering

Published: 2016-12-09T21:02:01Z

Content type: opinion

Language: en

Sources: [Square Corner Blog](<https://devfeed.tech/sources/square-corner-blog-medium.md>), [Square Corner Blog RSS Feed](<https://devfeed.tech/sources/square-corner-blog-rss-feed.md>)

Topics: [Hopper](<https://devfeed.tech/topics/hopper.md>), [Computer science](<https://devfeed.tech/topics/computer-science.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [community](<https://devfeed.tech/tags/community.md>), [computer-science](<https://devfeed.tech/tags/computer-science.md>), [conference](<https://devfeed.tech/tags/conference.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [events](<https://devfeed.tech/tags/events.md>), [hopper](<https://devfeed.tech/tags/hopper.md>), [intern](<https://devfeed.tech/tags/intern.md>), [open](<https://devfeed.tech/tags/open.md>), [team](<https://devfeed.tech/tags/team.md>), [women-in-tech](<https://devfeed.tech/tags/women-in-tech.md>)

### AI overview

Square employees reflect on attending the Grace Hopper Celebration of Women in Computing, describing the company's participation, its WomEng community, and the event's influence on women in technology and collegiate engineering.

### Source excerpt

This fall, 25 Squares attended The Grace Hopper Celebration of Women in Computing (GHC). The event may have concluded in October, but the...