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Training a State-of-the-Art ImageNet-1K Visual Transformer Model using NVIDIA DGX SuperPOD

This post shows how the SOTA Visual Transformer model, VOLO, is trained on the NVIDIA DGX SuperPOD. VOLO_D5 model. 9 MIN READ
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Deploying NVIDIA Triton at Scale with MIG and Kubernetes

NVIDIA Triton can manage any number and mix of models, support multiple deep-learning frameworks, and integrate easily with Kubernetes for large-scale deployment. 24 MIN READ
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Accelerating AI Training with NVIDIA TF32 Tensor Cores

NVIDIA Ampere GPU architecture introduced the third generation of Tensor Cores, with the new TensorFloat32 (TF32) mode for accelerating FP32 convolutions and… 10 MIN READ
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Adding More Support in NVIDIA GPU Operator

Editor's note: Interested in GPU Operator? Register for our upcoming webinar on January 20th, "How to Easily use GPUs with Kubernetes". 6 MIN READ
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Enhancing Memory Allocation with New NVIDIA CUDA 11.2 Features

CUDA is the software development platform for building GPU-accelerated applications, providing all the components needed to develop applications targeting every… 9 MIN READ
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Supercharging the World’s Fastest AI Supercomputing Platform on NVIDIA HGX A100 80GB GPUs

Exploding model sizes in deep learning and AI, complex simulations in high-performance computing (HPC), and massive datasets in data analytics all continue to… 5 MIN READ