--- 格式版本: 2 标题: "Playlist | CUDA, Libraries and Dev Tools Conference Sessions" 原文链接: "https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/" 发布日期: "2026-09-02" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Published Time: Wed, 02 Sep 2026 16:25:43 GMT" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 4 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-09-03T01:24:56+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-09-03T01:21:24+08:00" 入库时间: "2026-09-02T17:24:56.678Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://www.nvidia.com/gtc/" 匹配关键词: - "performance" - "GPU" - "AI" 相关厂家: - "NVIDIA" - "Meta" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 27 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文为NVIDIA GTC播放列表页面，仅列出CUDA、库和开发者工具相关会议会话，无超节点/AI Rack/机架级系统实质内容，也无新架构、产品、标准、客户或部署信息。虽来自NVIDIA官方，但属于导航/索引页，非可入库知识文章，命中导航页与正文不可用否决项。" AI质检模型: "zj-deepseek-v4-flash" AI质检时间: "2026-09-03T01:26:34+08:00" AI主题相关性: 2 AI来源权威性: 15 AI新颖性: 5 AI技术细节: 2 AI商业部署信号: 0 AI完整性: 3 AI评分提示词版本: "v17-精简生产版" AI评分提示词SHA256: "48fb9777f386026761b4873eaff30807694fb11e9b352d7c69bf2dfde750cc7d" AI评分知识库版本: "knowledge_base_v1-20260819+runtime.82" AI评分知识库SHA256: "3e2894004c6cfb364995ce0b1aba57c56546445847b8f9ac22f28f1d5005c8ff" AI评分知识库检索词: "[\"NVIDIA\",\"Nvidia GTC大会\",\"https://www.nvidia.com/gtc/\",\"RAS\",\"GPU\",\"Meta\",\"Intel\",\"CUDA\",\"URL\",\"GMT\",\"EN\",\"CI\"]" AI评分知识库命中: "[{\"id\":\"runtime-35f284698f34b54313c05e16\",\"title\":\"Restore LLM Inference Capacity in Seconds with Shadow Engine Recovery in NVIDIA Dynamo\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"NVIDIA\",\"https://www.nvidia.com/gtc/\",\"RAS\",\"GPU\",\"CUDA\",\"URL\",\"EN\",\"CI\"],\"rank\":-12.088192619965241},{\"id\":\"july-correct-0081\",\"title\":\"AAI 2026: 6th Gen AMD EPYC Server CPUs Power the Agentic Data Center\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"NVIDIA\",\"RAS\",\"GPU\",\"Intel\",\"URL\",\"EN\",\"CI\"],\"rank\":-10.532585659764775},{\"id\":\"july-correct-0001\",\"title\":\"全球首颗2nm GPU来了！苏姿丰甩出“最强AI机架”，CPU性能干翻英伟达 - 智东西\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"RAS\",\"GPU\",\"Meta\",\"EN\",\"CI\"],\"rank\":-10.215021597161616},{\"id\":\"runtime-2bfdcfdf1809b868538597ec\",\"title\":\"compute AMD Catches The Agentic AI Wave And Will Ride It Up Masterfully August 5, 2026\",\"sourceType\":\"ai_excellent_article\",\"time\":\"2026-08-05\",\"matchedTerms\":[\"NVIDIA\",\"RAS\",\"GPU\",\"Meta\",\"Intel\",\"CUDA\",\"EN\",\"CI\"],\"rank\":-10.076512119919343},{\"id\":\"runtime-5d07dc7b6b3ddbca50e6572d\",\"title\":\"NVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"NVIDIA\",\"https://www.nvidia.com/gtc/\",\"RAS\",\"GPU\",\"CUDA\",\"URL\",\"EN\",\"CI\"],\"rank\":-9.93977153196542}]" 采集批次: "2026年9月3日1点13分51秒" 采集批次ID: "20260903-011351-953" 去重键: "https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools" --- Title: Playlist | CUDA, Libraries and Dev Tools Conference Sessions URL Source: https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/ Published Time: Wed, 02 Sep 2026 16:25:43 GMT Markdown Content: Visit your regional NVIDIA website for local content, pricing, and where to buy partners specific to your country. [Continue](https://www.nvidia.com/) [](https://www.nvidia.com/en-us/ "Artificial Intelligence Computing Leadership from NVIDIA") * [](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/#) * [](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/#) * [](https://www.nvidia.com/en-us/account/) * [Log In](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/#)[LogOut](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/#) * [EN](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/#) * [EN](https://www.nvidia.com/en-us/on-demand/) * [简中](https://www.nvidia.cn/on-demand/) * [日本語](https://www.nvidia.com/ja-jp/on-demand/) * [한국어](https://www.nvidia.com/ko-kr/on-demand/) * [繁中](https://www.nvidia.com/zh-tw/on-demand/) [NVIDIA On-Demand](https://www.nvidia.com/en-us/on-demand/) [Featured Playlists](https://www.nvidia.com/en-us/on-demand/featured-playlist/) [My Channel](https://www.nvidia.com/en-us/on-demand/my-profile/) [FAQ](https://www.nvidia.com/en-us/on-demand/faq/) [Advanced Search](https://www.nvidia.com/en-us/on-demand/search/?q=-&sort=relevance&headerText=All%20Sessions&expandFilter=true) * [Featured Playlists](https://www.nvidia.com/en-us/on-demand/featured-playlist/) * [My Channel](https://www.nvidia.com/en-us/on-demand/my-profile/) * [FAQ](https://www.nvidia.com/en-us/on-demand/faq/) * [Advanced Search](https://www.nvidia.com/en-us/on-demand/search/?q=-&sort=relevance&headerText=All%20Sessions&expandFilter=true) [](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/# "Menu") [](https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/# "Menu") * [Featured Playlists](https://www.nvidia.com/en-us/on-demand/featured-playlist/) * [My Channel](https://www.nvidia.com/en-us/on-demand/my-profile/) * [FAQ](https://www.nvidia.com/en-us/on-demand/faq/) * [Advanced Search](https://www.nvidia.com/en-us/on-demand/search/?q=-&sort=relevance&headerText=All%20Sessions&expandFilter=true) ## CUDA, Libraries and Dev Tools Conference Sessions 17 sessions [39:33 ![Image 1: Architects of the Accelerated Age: How CUDA Builders Changed the World (and How You’re Next)](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_ljhr8h2a/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82416?playlistId=gtc26-cuda-libraries-and-dev-tools) Panel [Architects of the Accelerated Age: How CUDA Builders Changed the World (and How You’re Next)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82416?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 paulius micikevicius, Software Engineer, Meta Superintelligence Labs Kate Clark, Distinguished DevTech Engineer, NVIDIA Joe Stam, Head of Research Technology, Core Strategies , Jump Trading Stephen Jones (SW), CUDA Architect, NVIDIA Wen-Mei Hwu, Sr. Distinguished Research Scientist, Senior Distinguished Research Scientist and Senior Research Director at NVIDIA The world was changed by creators who wrote the first kernels and turned raw potential into reality. Now, they are sharing the blueprints. Join us for an unfiltered look at CUDA’s impact with prolific creators who have redefined the boundaries of… [44:27 ![Image 2: CUDA: New Features and Beyond](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_kbdc8erc/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81859?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [CUDA: New Features and Beyond](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81859?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Stephen Jones (SW), CUDA Architect, NVIDIA The CUDA platform is the foundation of the GPU computing ecosystem. Every application and framework that uses the GPU does so through CUDA's libraries, compilers, runtimes and language—which means CUDA is growing as fast as its… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81535?playlistId=gtc26-cuda-libraries-and-dev-tools) Connect With the Experts [CUDA Developer Best Practices](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81535?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Bryce Lelbach, Principal Architect, NVIDIA Ashwin Srinath, Senior Software Engineer, NVIDIA Georgii Evtushenko, Sr. Software Engineer, NVIDIA Jonathan Bentz, CUDA Technical Marketing Engineer, NVIDIA Jonathan Dekhtiar, Sr. CUDA Python Engineer, NVIDIA Jaydeep Marathe, Principal Software Engineer, NVIDIA Jake Hemstad, Software Engineering Manager, NVIDIA Leo Fang, Python CUDA Tech Lead, NVIDIA Nader Al Awar, Senior Software Engineer, NVIDIA Rafael Campana, Sr. Engineering Director of CUDA Developer Tools, NVIDIA Trent Nelson, Principal Software Engineer, NVIDIA Vyas Ramasubramani, Sr. Systems Software Engineer, NVIDIA Join this live Q&A session with some of NVIDIA’s own CUDA developers to demystify the process of building real-world CUDA applications. From utilizing CUDA accelerated libraries, profilers, and debugging tools to setting up CI pipelines,… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-dliw82265?playlistId=gtc26-cuda-libraries-and-dev-tools) Full-Day Workshop [Fundamentals of GPU-Accelerated Workflows with CUDA Python](https://www.nvidia.com/en-us/on-demand/session/gtc26-dliw82265?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Bryce Lelbach, Principal Architect, NVIDIA Katrina Riehl, Principal Technical Product Manager, NVIDIA This course delivers a hands-on introduction to GPU-accelerated computing in Python, empowering developers to build fast, scalable applications using NVIDIA’s CUDA ecosystem. Through guided notebooks, participants master CuPy for array… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81549?playlistId=gtc26-cuda-libraries-and-dev-tools) Connect With the Experts [What's in Your Developer Toolbox? CUDA, AI, and Graphics Profiling, Optimization, and Debugging…](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81549?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Aurelio Reis, Director of Graphics Developer Tools, NVIDIA Gaoyan Xie, Sr. Manager of Software Engineering, NVIDIA Holly Wilper, Manager, System Software Tools, NVIDIA Jackson Marusarz, Technical Product Manager, NVIDIA Magnus Strengert, Software Engineering Manager, NVIDIA Rafael Campana, Sr. Engineering Director of CUDA Developer Tools, NVIDIA Victor da Cruz Ferreira, Senior Software Engineer, NVIDIA Zbigniew Kondolewicz, Senior Software Developer, NVIDIA Several experts from the tools development and management teams will be available to talk about getting started, best practices, and advanced techniques for application debugging and optimization with NVIDIA developer tools. You can ask… [39:18 ![Image 3: Accelerated Building Blocks for Next-Generation AI+HPC Workloads](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_06y0mmhk/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81792?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Accelerated Building Blocks for Next-Generation AI+HPC Workloads](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81792?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Heidi Poxon, Director of Product, HPC Software, NVIDIA Embracing next-generation technology like AI-infused scientific workflows involves blending familiar building blocks with innovation, timeliness, and purpose. Whether it's models pre-trained on petabyte-scale data for common forecasting tasks, or… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81771?playlistId=gtc26-cuda-libraries-and-dev-tools) Connect With the Experts [How to Run and Optimize Your Workloads on the NVIDIA Grace and Vera CPUs](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81771?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Holly Wilper, Manager, System Software Tools, NVIDIA Hans Mortensen, Grace Product Specialist – NVIDIA Solutions Architecture, NVIDIA Lukas Alt, DevTech Engineer, NVIDIA Mathias Wagner, Sr. Developer Technology Engineer, NVIDIA Matthias Langer, Sr. AI and Developer Technology Engineer, NVIDIA Yuzhong Wen, Sr. DevTech Engineer, NVIDIA Join us to explore how NVIDIA's latest generation of ARM-based CPUs can boost data center performance and energy efficiency. We'll help you optimize your applications for the current NVIDIA Grace architecture while providing insights into… [36:55 ![Image 4: Accelerate Open Science: Incorporating CUDA Into the SciPy Ecosystem](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_u9l7jeg1/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82113?playlistId=gtc26-cuda-libraries-and-dev-tools) Panel [Accelerate Open Science: Incorporating CUDA Into the SciPy Ecosystem](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82113?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Gaël Varoquaux, Co-Founder, :probabl. Katrina Riehl, Principal Technical Product Manager, NVIDIA Ianna Osborne, Research Software Engineer, Princeton University Leo Fang, Python CUDA Tech Lead, NVIDIA Travis Oliphant, CEO, OpenTeams As GPUs become central to scientific Python workloads, SciPy-ecosystem projects—including NumPy, SciPy, and scikit-learn—face the challenge of adopting CUDA without sacrificing usability, portability, or community values. This panel brings… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes82212?playlistId=gtc26-cuda-libraries-and-dev-tools) Connect With the Experts [Boost Data Science Pipelines With Accelerated Libraries](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes82212?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Bobby Evans, Distinguished Software Engineer, NVIDIA Alexandria Barghi, Senior Software Engineer, NVIDIA Greg Kimball, Software Engineering Manager, NVIDIA Divye Gala, Senior Software Engineer, NVIDIA Vyas Ramasubramani, Sr. Systems Software Engineer, NVIDIA Drop into these walk-up office hours to meet the experts building NVIDIA’s CUDA-X data science libraries and talk through your end-to-end pipeline needs. ​Get practical guidance on where cuDF, cuML, cuGraph, and GPU-accelerated Spark can boost… [38:07 ![Image 5: Accelerate Engineering Simulations with NVIDIA cuDSS](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_0uhrzy90/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81824?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Accelerate Engineering Simulations with NVIDIA cuDSS](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81824?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Azi Riahi, Principal Product Manager, NVIDIA NVIDIA CUDA Direct Sparse Solver (cuDSS) is increasingly being adopted in large-scale simulations for engineering and design, such as those pertinent to electronic engineering automation (EDA) and computer-aided engineering (CAE). In this… [40:36 ![Image 6: Accelerate GPU Scientific Computing With nvmath-python](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_f78xjv77/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81581?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Accelerate GPU Scientific Computing With nvmath-python](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81581?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Aart Bik, Distinguished Engineer, NVIDIA Sergey Maydanov, Sr. Software Engineering Manager, NVIDIA In 2024, NVIDIA unveiled nvmath-python, a library designed to bridge the gap between Python scientific community and NVIDIA CUDA-X math libraries, and it’s now generally available. You’ll learn what makes nvmath-python a useful addition… [36:34 ![Image 7: Real-Time Science and Engineering With AI Physics and Kit-CAE](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_tl7k6a5t/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81781?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Real-Time Science and Engineering With AI Physics and Kit-CAE](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81781?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Jeff Larkin, HPC Architect, NVIDIA Physical engineering is moving from static reports and siloed workflows to real‑time, interactive insight. This session shows how AI physics meets simulation‑driven engineering by putting NVIDIA’s GPU‑accelerated libraries and NVIDIA Omniverse… [36:45 ![Image 8: cuEST: Accelerating Quantum Chemistry on GPUs](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_zek933kl/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81770?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [cuEST: Accelerating Quantum Chemistry on GPUs](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81770?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Anders Blom, Technical Product Manager, Synopsys Robert Parrish, Sr. Engineering Manager, NVIDIA Gaussian-basis quantum chemistry on NVIDIA GPUs is primed to change the world. Join this session to learn about new technologies and offerings from NVIDIA that help accelerate this paradigm shift. [01:39:45 ![Image 9: How to use NVIDIA Warp to Build GPU-Accelerated Computational Physics Simulations](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_t7koy8pb/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-dlit81837?playlistId=gtc26-cuda-libraries-and-dev-tools) Training Lab [How to use NVIDIA Warp to Build GPU-Accelerated Computational Physics Simulations](https://www.nvidia.com/en-us/on-demand/session/gtc26-dlit81837?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Eric Shi, Sr. Engineering Manager, NVIDIA Mohammad Mohajerani, Sr. Product Manager, NVIDIA Sheel Nidhan, Sr. Technical Marketing Engineer, NVIDIA Discover how NVIDIA Warp enables the next generation of GPU-accelerated physics, geometry processing, and differentiable programming. This training lab introduces Warp’s core capabilities and modules, then moves into a hands-on notebook where… [37:53 ![Image 10: Accelerating Industrial Engineering: From Product Design to Manufacturing in the AI Supercomputing Era](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_zf8ln5u8/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82017?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Accelerating Industrial Engineering: From Product Design to Manufacturing in the AI…](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82017?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Christoph Meyer, Chief Program Officer, McLaren Automotive Neil Ashton, Distinguished Engineer, NVIDIA Accelerated computing and AI supercomputing are redefining industrial engineering, spanning computational engineering (CAE) to semiconductor design and manufacturing. Together, these fields drive how the world conceives, simulates,… [36:55 ![Image 11: Python All the Way Down: Speed-of-Light CUDA Without Leaving Python](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_0lwxnq03/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81531?playlistId=gtc26-cuda-libraries-and-dev-tools) Talk [Python All the Way Down: Speed-of-Light CUDA Without Leaving Python](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81531?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Ashwin Srinath, Senior Software Engineer, NVIDIA Ianna Osborne, Research Software Engineer, Princeton University How would you write a Python library that uses CUDA today? Most Python GPU libraries—PyTorch, CuPy, RAPIDS, and others—still build on CUDA C++ because many core CUDA building blocks have only ever existed in C++. That’s now changing. New… [](https://www.nvidia.com/en-us/on-demand/session/gtc26-qa81741?playlistId=gtc26-cuda-libraries-and-dev-tools) Q&A With NVIDIA Experts [Ask the Experts: Applications Built for Scale With cuPyNumeric](https://www.nvidia.com/en-us/on-demand/session/gtc26-qa81741?playlistId=gtc26-cuda-libraries-and-dev-tools) March 2026 Bo Dong, Principal Technical Product Manager, NVIDIA Andy Terrel, CUDA Python Product Lead, NVIDIA Irina Demeshko, Sr. Software Engineer, NVIDIA Manolis Papadakis, Software Engineering Manager, Legate Framework, NVIDIA Shriram Jagannathan, Engineer, NVIDIA Quynh Nguyen, HPC and AI Alliance Manager, NVIDIA Want to understand how Python scales efficiently across GPUs and clusters? Join NVIDIA experts for a live, classroom-style Q&A on cuPyNumeric, the technology that extends NumPy to distributed GPU environments. 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Join NVIDIA experts for a live, classroom-style Q&A on cuPyNumeric, the technology that extends NumPy to distributed GPU environments. In this session, you’ll have the… Press space bar to start a drag. When dragging you can use the arrow keys to move the item around and escape to cancel. Some screen readers may require you to be in focus mode or to use your pass through key