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DTSTART;TZID=America/New_York:20260618T091500
DTEND;TZID=America/New_York:20260618T163000
DTSTAMP:20260626T161805Z
CREATED:20260512T040755Z
LAST-MODIFIED:20260626T161805Z
UID:24321-1781774100-1781800200@www.cambridgecomputer.com
SUMMARY:AI & HPC Day at George Washington University
DESCRIPTION:Description:\nJoin Cambridge and the GW Information Technology (GW IT) team on Thursday\, June 18th for an immersive exploration of high-performance computing and artificial intelligence. \nAs part of the national GPU in EDU Seminar Series\, Cambridge Computer and GW are bringing their expertise to GWU’s Foggy Bottom campus in Washington\, DC for an event hosted by the GW Information Technology team. This program is designed for faculty\, researchers\, and students who are looking to leverage the power of GPUs to accelerate discovery and innovation — supported by GW’s high-performance network infrastructure through CAAREN. \nThe day features expert-led presentations and hands-on demonstrations at the forefront of AI and data science in academic research. Whether you are just getting started with GPU computing or looking to scale an existing project\, this is your opportunity to connect with industry leaders and GW peers\, exchange ideas\, and leave with practical strategies to accelerate what comes next. \n			\n				\n				\n				\n				\n				Agenda:\nGPU in EDU Track\n\n9:15 AM | Morning Welcome – Clark Gaylord (GWU)\n9:30 AM | Ensuring Reproducibility in AI: Declarative Tools for Managing Software Stacks and Workflows – Dr. Christopher S. Simmons (Cambridge Computer)\n10:30 AM | Short Break\n10:45 AM | Tutorial: Implementing Open-Source LLMs in Research Computing: From Model Selection to On-Premises Deployment (Part 1 of 2) – Dr. Christopher S. Simmons (Cambridge Computer)\n12 PM – 1 PM | Lunch\n1 PM | Introduction\, Welcome & CAAREN Overview – Clark Gaylord (GWU)\n1:30 PM | Keynote: AI and HPC Roadmaps for Research Computing – Dr. Christopher S. Simmons (Cambridge Computer)\n2:15 PM | Short Break\n2:30 PM | Tutorial: Implementing Open-Source LLMs in Research Computing: From Model Selection to On-Premises Deployment (Part 2 of 2) – Dr. Christopher S. Simmons (Cambridge Computer)\n3:30 PM | GWU Presentations:\n\nGPU Computation: Practice and Experience – Speaker: Adam Wong (GWU)\nGPUs and GWU: Infrastructure\, Access\, and Research Impact – Speaker: Dr. Glen MacLachlan (GWU)\n\n\n4:30 PM | Presentation: AMD CPU and GPU Updates – Speaker: Zlatko Pozderac (AMD)\n\nJoin us for a networking happy hour following the day’s presentations and lectures! \nHPC User Group Track\n\n1 PM | Introduction\, Welcome & CAAREN Overview – Clark Gaylord (GWU)\n1:30 PM | Keynote: AI and HPC Roadmaps for Research Computing – Dr. Christopher S. Simmons (Cambridge Computer)\n2:30 PM | Presentation & Discussion: Secure Computing – Moderators: Shawn Suter (JHU) & Dr. Alastair Neil (GMU)\n3:30 PM | Discussion: Storage in 2026 – Moderators: Clark Gaylord (GWU) & Derek Yarnell (UMD)\n4:30 PM | Power Cooling – Joe Biondo (JHU ARCH)\n\nJoin us for a networking happy hour following the day’s presentations and lectures! \n \nSponsored by:
URL:https://www.cambridgecomputer.com/event/ai-hpc-day-at-george-washington-university/
LOCATION:George Washington University\, 800 22nd St NW\, Washington D.C.\, DC\, 20052\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/05/GPU-in-EDU-at-George-Washington-University.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20251117T110000
DTEND;TZID=America/Chicago:20251117T130000
DTSTAMP:20260421T003154Z
CREATED:20260421T002431Z
LAST-MODIFIED:20260421T003154Z
UID:24253-1763377200-1763384400@www.cambridgecomputer.com
SUMMARY:Implementing Open-Source LLMs
DESCRIPTION:Overview\nThis meeting is the 2nd annual in-person gathering of the GPU Innovators User Community. In our inaugural meeting last year in Atlanta\, we packed the room with passionate discussions about NVIDIA’s Grace Hopper and Blackwell architectures—the powerhouse hardware that makes today’s AI revolution possible. This year\, we’re taking the next logical step in our community’s journey: transitioning from metal to models. \nTL;DR\nWe’ll tackle the questions keeping you up at night—which models fit your research needs\, what hardware specifications actually matter\, and how to deploy these systems using the open-source tools you already trust. \nLunch is served afterwards at the Blues Museum down the street. \nIntended Audience \nThis talk is designed for research computing professionals\, HPC administrators\, academic researchers\, and AI enthusiasts seeking practical guidance on deploying open-source LLMs\, selecting appropriate models\, and integrating them into existing research computing infrastructure. \nSession Description \nThe rapid evolution of open-source large language models presents researchers with unprecedented opportunities to deploy powerful AI capabilities while maintaining complete control over sensitive data and computational workflows. This tutorial addresses the critical challenge facing research computing centers: how to navigate the complex landscape of open-source LLMs to make informed decisions about model selection\, hardware requirements\, and deployment strategies that align with existing HPC infrastructure and research objectives. \nThe session begins with a systematic exploration of leading open-source model families\, including DeepSeek’s reasoning-optimized variants\, Meta’s Llama ecosystem\, Google’s efficiency-focused Gemma models\, and specialized options like MedGemma for healthcare applications. Attendees will learn to evaluate models based on benchmark performance\, memory requirements\, and domain-specific capabilities\, while understanding the critical relationship between model parameters\, precision formats (FP16/FP8/FP4)\, and GPU memory allocation. Beyond model selection\, participants will explore the open-source framework ecosystem\, comparing GUI tools like LM Studio for rapid prototyping with high-performance CLI engines like vLLM and SGLang\, which are suitable for SLURM integration and multi-GPU scaling. The session concludes with an introduction to Retrieval-Augmented Generation (RAG) pipelines\, which enable researchers to query private document collections. This approach provides a key differentiator from commercial LLM services\, ensuring data privacy and institutional control while extending model capabilities with domain-specific knowledge. \nIf you attended this talk at PEARC25\, you might still find this content worth your while—a LOT has changed since then! \nFree Lunch \nAfter the seminar\, please join us just steps away at the National Blues Museum for a free BBQ lunch\, drinks and live music! Blues\, BBQ & Beer Event
URL:https://www.cambridgecomputer.com/event/implementing-open-source-llms/
LOCATION:Missouri Athletic Club\, 405 Washington Ave.\, St. Louis\, 63102\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/04/GPU_in_EDU_SC25.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251029
DTEND;VALUE=DATE:20251030
DTSTAMP:20260202T235603Z
CREATED:20260202T235603Z
LAST-MODIFIED:20260202T235603Z
UID:24181-1761696000-1761782399@www.cambridgecomputer.com
SUMMARY:GPU in EDU at University of Minnesota
DESCRIPTION:This one-day event\, presented in collaboration with the Minnesota Supercomputing Institute at the University of Minnesota\, features Dr. Christopher S. Simmons leading comprehensive sessions that equip academic researchers with a complete framework for implementing reproducible AI and scientific workflows. \nVisit Event Page to Register → \nAll registrants will receive Zoom meeting information for remote participation and a link to the recorded sessions.
URL:https://www.cambridgecomputer.com/event/gpu-in-edu-at-university-of-minnesota/
LOCATION:Coffman Memorial Union\, President’s Room\, 300 Washington Ave. S.E.\, Minneapolis\, MN\, 55455\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/png:https://www.cambridgecomputer.com/wp-content/uploads/2026/02/GPU-in-EDU-University-of-Minnesota.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250515T100000
DTEND;TZID=America/Los_Angeles:20250515T160000
DTSTAMP:20250416T174418Z
CREATED:20250407T221230Z
LAST-MODIFIED:20250416T174418Z
UID:23968-1747303200-1747324800@www.cambridgecomputer.com
SUMMARY:GPU in EDU at University of Washington
DESCRIPTION:Join Cambridge Computer\, NVIDIA\, and the UW-IT Research Computing Team for a day of innovation and learning at the University of Washington. This hybrid event is part of our national GPU in EDU Seminar Series\, focusing on the expanding role of AI and data science in academic research and education. \nWhat to Expect:\n\nExpert Presentations on reproducible software pipelines\, GPU computing services\, and NVIDIA RAPIDS\nHands-on Demonstrations showcasing practical GPU implementations\nNetworking Opportunities with industry leaders and academic researchers\nQ&A Sessions with Cambridge\, NVIDIA\, and UW-IT specialists\n\nFeatured speakers include Dr. Christopher Simmons (Cambridge Computer)\, Dr. Melisa Alkan (NVIDIA)\, and Dr. Kristen Finch (UW-IT Research Computing). \nWhether you’re new to GPU computing or scaling advanced research\, this seminar offers valuable insights for accelerating your research workflows. \nVisit Event Page to Register → \nAll registrants will receive Zoom meeting information for remote participation.
URL:https://www.cambridgecomputer.com/event/gpu-in-edu-at-university-of-washington/
LOCATION:UW Tower\, 4333 Brooklyn Ave NE\, Seattle\, WA\, 98105\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2025/04/GPU_in_EDU_at_UW.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250204T130000
DTEND;TZID=America/New_York:20250204T180000
DTSTAMP:20260421T002057Z
CREATED:20260420T235532Z
LAST-MODIFIED:20260421T002057Z
UID:24249-1738674000-1738692000@www.cambridgecomputer.com
SUMMARY:GPU in EDU: Dartmouth College
DESCRIPTION:Overview\n\n\n\nPresentations and discussions about HPC & AI infrastructure for science and higher education \n\n\n\n\nThe day will feature a mix of presentations from the Cambridge and Dartmouth teams\, along with open discussions with attendees. Everyone is welcome to join the Happy Hour at the end of the event at Murphy’s! \n\n\n\nAgenda\n1:00 PM – 2:00 PM — Goldstein 105 Occom Commons (including lunch) \n\nRoadmap – NVIDIA Products & Highlights 2025 – Cambridge & NVIDIA\nDiscussion – How to Leverage GH200s (specifically memory)\nDiscussion – Over-Subscribing Systems and Unified Memory\n\n2:00 PM – 2:15 PM — Break; move to Filene \n2:15 PM – 3:15 PM — Moore Hall B13 Filene Auditorium \n\nPresentation – GPUs/AI – A Scientist’s Perspective – Chris Simmons\nSneak Peek – Grace Blackwell\n\n3:15 PM – 4:00 PM — Moore Hall B13 Filene Auditorium Dartmouth Presentation \n\nReviewing chat.dartmouth.edu and ai.dartmouth.edu – Dartmouth Team\nIntroduction to Research Computing AI Offerings and Real-world Applications – Simon Stone\nAPI access to chat.dartmouth.edu – Jonathan Crossett\nIn-depth Coverage & Future Plans for chat.dartmouth.edu – Tivon Luker\nQ & A – Jonathan Crossett\, Simon Stone\, Tivon Luker\n\n4:00 PM – 4:15 PM — Break \n4:15 PM – 5:00 PM — (OPTIONAL) Farewell to AFS presentation \n5:00 PM – 6:00 PM — Murphy’s On the Green \n\nHappy Hour @ Murphy’s – Sponsored by Dartmouth
URL:https://www.cambridgecomputer.com/event/gpu-in-edu-dartmouth-college/
LOCATION:Dartmouth College\, 3 Maynard St\, Hanover\, NH\, 03755\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/04/GPU_in_EDU_Dartmouth.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241203T100000
DTEND;TZID=America/New_York:20241203T163000
DTSTAMP:20260421T003624Z
CREATED:20260421T003624Z
LAST-MODIFIED:20260421T003624Z
UID:24258-1733220000-1733243400@www.cambridgecomputer.com
SUMMARY:NVIDIA Day at Columbia University
DESCRIPTION:Overview\nPresentations and discussions about AI and data science in research and education. \nThe morning session will focus on NVIDIA overviews and topics of particular concern to IT Professionals. The afternoon will focus on Researcher workloads with additional presentations from NVIDIA\, Cambridge\, and CUIT as well as opportunities for open discussion. All are welcome to join throughout the day and to come and go as your schedule allows! \nRoom Location: Davis Auditorium\, Schapiro CEPSR \nAbout Cambridge \nCambridge Computer provides IT infrastructure solutions with a focus on the needs of higher education and research computing. We work with our clients and vendors to specify\, sell\, and deploy hardware. Projects are as simple as individual workstations and as complex as HPC/GPU compute clusters. \nAbout NVIDIA \nWe pioneered accelerated computing to tackle challenges no one else can solve. With NVIDIA\, healthcare institutions can harness the power of AI and high-performance computing to define the future of medicine. NVIDIA engineers the most advanced chips\, systems\, and software for the AI factories of the future. We build new AI services that help institutions create their own AI factories.
URL:https://www.cambridgecomputer.com/event/nvidia-day-at-columbia-university/
LOCATION:Davis Auditorium\, Schapiro CEPSR\, 530 West 120th Street\, New York\, NY\, 10027\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/04/GPU_in_EDU_Columbia-University.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241119T070000
DTEND;TZID=America/New_York:20241119T100000
DTSTAMP:20241107T061716Z
CREATED:20241106T022104Z
LAST-MODIFIED:20241107T061716Z
UID:23136-1731999600-1732010400@www.cambridgecomputer.com
SUMMARY:GPU in EDU Higher Ed Breakfast Meetup and Panel
DESCRIPTION:Join us for a morning of insights and discussion with Cambridge and NVIDIA at the “GPU in EDU” Breakfast Meetup & Panel Discussion. \nBreakfast & Latte Services\n7:00 AM – 10:00 AM \nPanel with Harvard Medical School & University of California\, San Francisco\n8:00 AM – 9:30 AM \nQ&A\n9:30 AM – 10:00 AM \n\n\n 
URL:https://www.cambridgecomputer.com/event/gpu-in-edu-higher-ed-breakfast-meetup-and-panel/
LOCATION:College Football Hall of Fame\, 250 Marietta Street NW\, Atlanta\, GA\, 30313\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2024/10/GPU_in_EDU_SC24-Breakfast.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240718
DTEND;VALUE=DATE:20240719
DTSTAMP:20260420T235147Z
CREATED:20241017T195607Z
LAST-MODIFIED:20260420T235147Z
UID:22836-1721260800-1721347199@www.cambridgecomputer.com
SUMMARY:AI Futures at Harvard Medical School
DESCRIPTION:Cambridge and NVIDIA had a full house at Harvard Med for the seminar entitled AI Futures at Harvard Medical School. GPU in EDU is a seminar series co-produced by NVIDIA and Cambridge Computer. We travel to universities and research institutions across the country to share ideas and insights related to AI and ML at the intersection of science and IT infrastructure. The content of each session is tailored to the specific interests of the institution hosting the event. Harvard Med chose to focus on deep learning for genomics\, NVIDIA software frameworks\, and GPU resource management. \nWe’d like to thank our friends at Harvard\, Run:ai\, and NVIDIA for making this event possible. Their support and collaboration were instrumental in making it a memorable and informative event. Special thanks for Run:ai for co-sponsoring the event and sharing insights into their amazing technology for pooling and scheduling GPU resources. We’d also like to thank Christos Alexiadis (Cambridge) and Eliot Eshelman (NVIDIA) for all their work behind the scenes. \nAgenda\nWelcome Session (10:00am – 10:15 am) Presented by: Eliot Eshelman (NVIDIA) & Jose Alvarez (Cambridge) \nPart 1. Deep Learning & Genomics (10:15 am – 12:30 pm) 10:15 – 11:00 am – Training\, Tuning\, & Deploying large deep learning models (45 mins) – Huiwen Ju (NVIDIA) 11:00 – 11:45 am – Deep learning applications in proteomics (45 mins) – Glen Otero (Cambridge) 11:45 am – 12:30 pm – GPU-based acceleration of genomic data. (45 mins) – Glen Otero (Cambridge) \nLunch break (12:30 pm – 1:30 pm) We will be ordering Milk Street Cafe for our networking/lunch hour portion of the agenda. \nPart 2: New NVIDIA Software Frameworks for Life Sciences (1:30 pm – 2:30 pm) \n\nSurvey of NVIDIA software frameworks in healthcare & life sciences (1 hour) – Huiwen Ju (NVIDIA)\n\nNIMs for standardized\, efficient Generative AI deployments (hands-on with https://ai.nvidia.com/)\nBioNeMo for AI-driven drug discovery\nMONAI the open-source framework for AI in medical imaging\nVISTA-2D AI Foundation model for cell segmentation\nRAPIDS for accelerated data science\nFLARE for federated learning\n\n\n\nCoffee Break (2:30 pm – 2:45 pm) \nPart 3. GPU Utilization (2:45 pm – 3:45 pm) \n\nSummary of latest NVIDIA architectures (5 minutes) – Brad Palmer (NVIDIA)\n\nH200\, B200\, GH200\, GB200\n\n\nGPU Monitoring and Management (25 minutes) – Brad Palmer (NVIDIA)\n\nCollecting and Displaying GPU performance data\nManaging GPU configurations across a cluster\n\n\nGPU Resource Management (30 mins) – Brett Wagner (Run:ai)
URL:https://www.cambridgecomputer.com/event/ai-futures-at-harvard-medical-school/
LOCATION:Countway Library\, Harvard Medical School\, 695 Huntington Ave.\, Boston\, 02115
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2024/10/GPU_in_EDU_at_HMS.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240402
DTEND;VALUE=DATE:20240403
DTSTAMP:20241018T025231Z
CREATED:20241018T025016Z
LAST-MODIFIED:20241018T025231Z
UID:22952-1712016000-1712102399@www.cambridgecomputer.com
SUMMARY:GPU in EDU at Carnegie Mellon University
DESCRIPTION:Cambridge Computer and NVIDIA teamed to lead a seminar last week at Carnegie Mellon University to discuss how new HPC and GPU architectures impact research computing in higher ed. We had a full room plus a bunch of people attending remotely. There was some lively debate and a lot of great ideas shared. We gave our own version of the NVIDIA GTC recap and led a discussion on the new chip architectures (Grace\, Hopper\, Blackwell). We also had presentations from Nvidia on the various products and services that they offer that are lesser known to their client base. This was a great chance for different stakeholders in the university to get together in person and bat around ideas\, common challenges\, etc.
URL:https://www.cambridgecomputer.com/event/gpu-in-edu-at-carnegie-mellon-university/
LOCATION:Carnegie Mellon University\, 4902 Forbes Ave.\, Pittsburg\, PA\, 15213\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2024/10/GPU_in_EDU_Carnegie_Mellon.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221012T090000
DTEND;TZID=America/New_York:20221012T160000
DTSTAMP:20260421T004648Z
CREATED:20260421T004452Z
LAST-MODIFIED:20260421T004648Z
UID:24261-1665565200-1665590400@www.cambridgecomputer.com
SUMMARY:HPC AI Day - Stony Brook University
DESCRIPTION:Overview\nA follow-up to Cambridge Computer’s HPC AI Day @ PEARC 2022 \nCambridge is looking forward to uniting industry leaders at Stony Brook University’s campus for a 1-day series of presentations and workshops. \nLocation: CEWIT Conference Room \nAgenda\n*Times subject to change \n8:00 AM – Welcome & Coffee Hour \n9:00 AM – Nvidia & Research Computing \n\nThe DPU – Provide high-level overview\nNvidia Latest Product Announcements from GTC including Grace/Hopper\, L40 and RTX6000\nNvidia HPC Software Development Kits for AI based models\nQ&A\n\n10:30AM – **Break** \n10:45 AM – Run:ai – Building AI Infrastructure Right \n11:30 AM – **LUNCH** \n12:30 PM – AMD: CPU Roadmap & Software Stack\, ROCm & GPU Review \n\nOpen source tool for GPU Computing\n\n2:00 PM – **Break** \n2:15 PM – CIQ: Rocky Linux & Containers – Singularity Support \n3:00 PM – **Break** \n3:15 PM – Intel: CPU & HBM Roadmap & Software Research Stack – oneAPI \n\nHow the Intel® DPC++ Compatibility Tool assists in migrating your existing CUDA code to Data Parallel C++ (DPC++) code\nAbout DPC++\, based on ISO C++ and incorporates standard SYCL and community extensions to simplify data parallel programming.\nHow the tool ports both CUDA language kernels and library API calls
URL:https://www.cambridgecomputer.com/event/hpc-ai-day-stony-brook-university/
LOCATION:Gates and Hillman Centers\, 4902 Forbes Avenue\, Pittsburg\, PA\, 15213\, United States
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/04/GPU_in_EDU_Stony-Brook-University.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211202T083000
DTEND;TZID=America/New_York:20211202T103000
DTSTAMP:20260421T005219Z
CREATED:20260421T005126Z
LAST-MODIFIED:20260421T005219Z
UID:24266-1638433800-1638441000@www.cambridgecomputer.com
SUMMARY:GPU Direct at Clemson
DESCRIPTION:Overview\nRSVP today to receive your Grub Hub gift card Clemson Lunch & Learn with Vast Data & Cambridge Computer! \nClemson’s newest High-Performance Computing installation is a GPU Direct architecture connecting NVIDIA’s newest system\, the DGX A100\, to a high-performance storage array from VAST Data. \nThis supercomputer is available to you to increase your time-to-results and outcomes from your research. Perhaps you’ve asked yourself “what benefits are gained when I bypass the CPU and leverage GPU-Direct architecture?” or “what do I need to change about my process or code to leverage this system?” \nPlease join us for an interactive session\, we will dive into those questions and more! \nSchedule\n11:15 AM – Order your Grub Hub meal for 12:15pm delivery! \n11:30 AM – 12:15 PM – Session 1 \n\nWhy & When GPU Direct Architectures are Advantageous – Presented by Vast Data\nWhere Does it all Happen at Clemson? – Presented by Palmetto Storage Team\n\n12:15 PM – 12:45 PM – Lunch break w/ Grub Hub \n12:45 PM – 1:30 PM – Session 2 \n\nLeveraging GPU Direct – Presented by Cambridge Computer Professional Services Team\nHow do we use it? – Hands-on lab with Cambridge\, Vast and audience\nOur team will send the zoom link via calendar invitation upon registration or see below
URL:https://www.cambridgecomputer.com/event/gpu-direct-at-clemson/
LOCATION:Virtual
CATEGORIES:GPU in EDU
ATTACH;FMTTYPE=image/jpeg:https://www.cambridgecomputer.com/wp-content/uploads/2026/04/GPU_in_EDU_Clemson.jpg
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