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Title: GitHub - Sampson2016/server: The Triton Inference Server provides an optimized cloud and edge inferencing solution. · GitHub

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Description: The Triton Inference Server provides an optimized cloud and edge inferencing solution. - GitHub - Sampson2016/server: The Triton Inference Server provides an optimized cloud and edge inferencing solution.

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https://github.com/Sampson2016/server#documentation
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QuickStarthttps://github.com/Sampson2016/server/blob/main/docs/quickstart.md
Install Tritonhttps://github.com/Sampson2016/server/blob/main/docs/quickstart.md#install-triton-docker-image
Create Model Repositoryhttps://github.com/Sampson2016/server/blob/main/docs/quickstart.md#create-a-model-repository
Run Tritonhttps://github.com/Sampson2016/server/blob/main/docs/quickstart.md#run-triton
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Required Model Configurationhttps://github.com/Sampson2016/server/blob/main/docs/model_configuration.md#minimal-model-configuration
Maximum Batch Size - Batching and Non-Batching Modelshttps://github.com/Sampson2016/server/blob/main/docs/model_configuration.md#maximum-batch-size
Input and Output Tensorshttps://github.com/Sampson2016/server/blob/main/docs/model_configuration.md#inputs-and-outputs
Tensor Datatypeshttps://github.com/Sampson2016/server/blob/main/docs/model_configuration.md#datatypes
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Shape Tensorhttps://github.com/Sampson2016/server/blob/main/docs/model_configuration.md#shape-tensors
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client exampleshttps://github.com/triton-inference-server/client
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generate a GRPC client for many other languageshttps://github.com/triton-inference-server/client
optimizing performancehttps://github.com/Sampson2016/server/blob/main/docs/optimization.md
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Prometheus metrics endpointhttps://github.com/Sampson2016/server/blob/main/docs/metrics.md
deep learning exampleshttps://github.com/NVIDIA/DeepLearningExamples
explicitly manage what models are available by loading and unloading modelshttps://github.com/Sampson2016/server/blob/main/docs/model_management.md
GCPhttps://github.com/Sampson2016/server/blob/main/deploy/gcp/README.md
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NVIDIA FleetCommandhttps://github.com/Sampson2016/server/blob/main/deploy/fleetcommand/README.md
version 1 to version 2 migration informationhttps://github.com/Sampson2016/server/blob/main/docs/v1_to_v2.md
https://github.com/Sampson2016/server#developer-documentation
Buildhttps://github.com/Sampson2016/server/blob/main/docs/build.md
Protocols and APIshttps://github.com/Sampson2016/server/blob/main/docs/inference_protocols.md
Backendshttps://github.com/triton-inference-server/backend
Repository Agentshttps://github.com/Sampson2016/server/blob/main/docs/repository_agents.md
Testhttps://github.com/Sampson2016/server/blob/main/docs/test.md
built using Dockerhttps://github.com/Sampson2016/server/blob/main/docs/build.md#building-triton-with-docker
built without Dockerhttps://github.com/Sampson2016/server/blob/main/docs/build.md#building-triton-without-docker
test Tritonhttps://github.com/Sampson2016/server/blob/main/docs/test.md
create a Docker image containing a customized Tritonhttps://github.com/Sampson2016/server/blob/main/docs/compose.md
client libraries for Python and C++https://github.com/triton-inference-server/client
example clientshttps://github.com/triton-inference-server/client
HTTP/REST or GRPC protocolshttps://github.com/Sampson2016/server/blob/main/docs/inference_protocols.md
C APIhttps://github.com/Sampson2016/server/blob/main/docs/inference_protocols.md
Triton backendhttps://github.com/triton-inference-server/backend
DALIhttps://github.com/triton-inference-server/dali_backend
writing your own backendhttps://github.com/triton-inference-server/backend
C/C++https://github.com/triton-inference-server/backend/blob/main/README.md#triton-backend-api
Pythonhttps://github.com/triton-inference-server/python_backend
Triton repository agenthttps://github.com/Sampson2016/server/blob/main/docs/repository_agents.md
https://github.com/Sampson2016/server#papers-and-presentation
Maximizing Deep Learning Inference Performance with NVIDIA Model Analyzerhttps://developer.nvidia.com/blog/maximizing-deep-learning-inference-performance-with-nvidia-model-analyzer/
High-Performance Inferencing at Scale Using the TensorRT Inference Serverhttps://developer.nvidia.com/gtc/2020/video/s22418
Accelerate and Autoscale Deep Learning Inference on GPUs with KFServinghttps://developer.nvidia.com/gtc/2020/video/s22459
Deep into Triton Inference Server: BERT Practical Deployment on NVIDIA GPUhttps://developer.nvidia.com/gtc/2020/video/s21736
Maximizing Utilization for Data Center Inference with TensorRT Inference Serverhttps://on-demand-gtc.gputechconf.com/gtcnew/sessionview.php?sessionName=s9438-maximizing+utilization+for+data+center+inference+with+tensorrt+inference+server
NVIDIA TensorRT Inference Server Boosts Deep Learning Inferencehttps://devblogs.nvidia.com/nvidia-serves-deep-learning-inference/
GPU-Accelerated Inference for Kubernetes with the NVIDIA TensorRT Inference Server and Kubeflowhttps://www.kubeflow.org/blog/nvidia_tensorrt/
Deploying NVIDIA Triton at Scale with MIG and Kuberneteshttps://developer.nvidia.com/blog/deploying-nvidia-triton-at-scale-with-mig-and-kubernetes/
https://github.com/Sampson2016/server#contributing
CONTRIBUTING.mdhttps://github.com/Sampson2016/server/blob/main/CONTRIBUTING.md
contrib repohttps://github.com/triton-inference-server/contrib
https://github.com/Sampson2016/server#reporting-problems-asking-questions
https://stackoverflow.com/help/mcvehttps://stackoverflow.com/help/mcve
developer.nvidia.com/nvidia-triton-inference-serverhttps://developer.nvidia.com/nvidia-triton-inference-server
Readme https://github.com/Sampson2016/server#readme-ov-file
BSD-3-Clause license https://github.com/Sampson2016/server#BSD-3-Clause-1-ov-file
Contributing https://github.com/Sampson2016/server#contributing-ov-file
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