NVIDIA Triton Inference Server
E234124
NVIDIA Triton Inference Server is an open-source, production-ready platform for serving and scaling AI model inference across GPUs and CPUs with support for multiple frameworks and deployment environments.
All labels observed (2)
| Label | Occurrences |
|---|---|
| NVIDIA Triton Inference Server canonical | 7 |
| Triton Inference Server | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2111938 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NVIDIA Triton Inference Server Context triple: [NVIDIA DGX, supports, NVIDIA Triton Inference Server]
-
A.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
-
B.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
-
C.
PlaidML
PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
-
D.
Graphcore
Graphcore is a British semiconductor company that develops specialized intelligence processing units (IPUs) and systems designed to accelerate artificial intelligence and machine learning workloads.
-
E.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NVIDIA Triton Inference Server Target entity description: NVIDIA Triton Inference Server is an open-source, production-ready platform for serving and scaling AI model inference across GPUs and CPUs with support for multiple frameworks and deployment environments.
-
A.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
-
B.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
-
C.
PlaidML
PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
-
D.
Graphcore
Graphcore is a British semiconductor company that develops specialized intelligence processing units (IPUs) and systems designed to accelerate artificial intelligence and machine learning workloads.
-
E.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
- F. None of above. chosen
Statements (57)
| Predicate | Object |
|---|---|
| instanceOf |
AI inference server
ⓘ
model serving software ⓘ open-source software ⓘ |
| developer |
NVIDIA
ⓘ
linked to:
NVIDIA Corporation
|
| hasFeature |
GPU-aware scheduling
ⓘ
auto-scaling integration ⓘ dynamic model loading ⓘ model ensemble support ⓘ model repository ⓘ model warmup ⓘ request batching ⓘ |
| license |
BSD 3-Clause License
ⓘ
linked to:
BSD license
|
| officialWebsite | https://developer.nvidia.com/nvidia-triton-inference-server ⓘ |
| programmingLanguage |
C++
ⓘ
Python ⓘ |
| repositoryUrl | https://github.com/triton-inference-server/server ⓘ |
| supportsBatching | true ⓘ |
| supportsCloudPlatform |
NVIDIA AI Enterprise
ⓘ
linked to:
NVIDIA AI Enterprise software suite
NVIDIA DGX systems ⓘ
linked to:
NVIDIA DGX
major public clouds ⓘ |
| supportsConcurrentModelExecution | true ⓘ |
| supportsDeploymentEnvironment |
Docker
ⓘ
Kubernetes ⓘ bare metal ⓘ virtual machines ⓘ |
| supportsDynamicBatching | true ⓘ |
| supportsFormat |
C++ model
ⓘ
ONNX ⓘ Python model ⓘ TensorFlow GraphDef ⓘ TensorFlow SavedModel ⓘ
linked to:
TensorFlow SavedModel (via conversion)
TensorRT engine ⓘ
linked to:
NVIDIA TensorRT
TorchScript ⓘ
linked to:
PyTorch
|
| supportsFramework |
C++ backend
ⓘ
ONNX Runtime ⓘ OpenVINO ⓘ PyTorch ⓘ Python backend ⓘ TensorFlow ⓘ TensorRT ⓘ
linked to:
NVIDIA TensorRT
|
| supportsGRPCProtocol | true ⓘ |
| supportsHardware |
CPU
ⓘ
GPU ⓘ |
| supportsHTTPProtocol | true ⓘ |
| supportsMetrics |
CPU utilization
ⓘ
GPU utilization ⓘ Prometheus ⓘ request latency ⓘ throughput ⓘ |
| supportsModelType |
NLP models
ⓘ
computer vision models ⓘ recommendation models ⓘ |
| supportsModelVersioning | true ⓘ |
| supportsMultiModelServing | true ⓘ |
| useCase |
batch inference
ⓘ
online inference ⓘ real-time AI serving ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: NVIDIA Triton Inference Server Description of subject: NVIDIA Triton Inference Server is an open-source, production-ready platform for serving and scaling AI model inference across GPUs and CPUs with support for multiple frameworks and deployment environments.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.