How NVIDIA Uses GitLab
19 engineering articles about GitLab from NVIDIA's engineering team
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The article discusses how Continuous Integration and Continuous Delivery/Deployment (CI/CD) practices can be applied to network automation, particularly with Cumulus Linux and the NVIDIA Air digita...
The article discusses how NVIDIA Air facilitates network automation using tools like Ansible and Git, emphasizing the importance of coding, versioning, and automating network configurations.
The article discusses the advantages of using external file uploads for creating scalable and customizable network topologies in NVIDIA Air.
The article discusses how Qodo leverages NVIDIA DGX to innovate efficient code search through AI-powered agents.
Amit Bleiweiss
7 min read
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The article introduces NVIDIA Air, a cloud-based platform designed for simulating real-world data center environments, specifically tailored for AI workloads.
The article discusses the NVIDIA AI Workbench, a free development environment manager designed to facilitate frictionless collaboration and rapid prototyping in hybrid environments for data science...
NVIDIA AI Workbench is a free development environment manager that simplifies the use of GPUs on Windows, macOS, and Ubuntu for data science, machine learning, and AI projects.
The article discusses how hybrid retrieval-augmented generation (RAG) can optimize AI model performance while maintaining data privacy.
Shruthii Sathyanarayanan
7 min read
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The article explores the integration of SONiC (Software for Open Networking in the Cloud) with NVIDIA Air, highlighting its benefits for building networking infrastructure and proof of concepts (Po...
NVIDIA AI Workbench is a newly available toolkit designed to streamline AI and ML development for both novice and expert developers.
André Franklin
4 min read
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NVIDIA AI Workbench is now in beta, offering features that simplify the creation, sharing, and scaling of AI and machine learning workflows for enterprise developers.
Shruthii Sathyanarayanan
10 min read
Includes Code
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This article discusses the integration of CUDA Graphs into GROMACS 2023, a widely used molecular dynamics simulation package.
Alan Gray
12 min read
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The article discusses the significant advancements in multi-node scalability of GROMACS, a software package for biomolecular simulations, achieved through the introduction of GPU Particle-mesh Ewal...
Alan Gray
8 min read
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The article discusses the benefits of using pull requests in software development for collaboration and code review.
Fatos Morina
6 min read
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The article discusses how NVIDIA GPU Operator v22. 9 enhances Kubernetes orchestration by enabling GPU-accelerated virtual machines through KubeVirt and OpenShift Virtualization.
Charu Chaubal
4 min read
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The article discusses the role of Data Processing Units (DPUs) in modern data centers, highlighting NVIDIA's DOCA as a key framework for enabling innovation through ecosystem partnerships.
David Wills
4 min read
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This article discusses multi-GPU programming using Standard Parallel C++, focusing on the advantages of utilizing parallelism in C++ for accelerated computing.
The article explores the workings of Ethernet Virtual Private Network (EVPN) traffic flows, particularly focusing on the transition from traditional layer 2 environments to VXLAN driven by EVPN.
The article discusses how to enhance high-performance computing (HPC) applications using NVIDIA Nsight Compute and the Roofline performance model.
Jackson Marusarz
10 min read
Includes Code
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