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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Exafunction enhances the efficiency of your deep learning inference tasks, achieving up to a tenfold increase in resource utilization and cost savings. This allows you to concentrate on developing your deep learning application rather than juggling cluster management and performance tuning. In many deep learning scenarios, limitations in CPU, I/O, and network capacities can hinder the optimal use of GPU resources. With Exafunction, GPU code is efficiently migrated to high-utilization remote resources, including cost-effective spot instances, while the core logic operates on a low-cost CPU instance. Proven in demanding applications such as large-scale autonomous vehicle simulations, Exafunction handles intricate custom models, guarantees numerical consistency, and effectively manages thousands of GPUs working simultaneously. It is compatible with leading deep learning frameworks and inference runtimes, ensuring that models and dependencies, including custom operators, are meticulously versioned, so you can trust that you're always obtaining accurate results. This comprehensive approach not only enhances performance but also simplifies the deployment process, allowing developers to focus on innovation instead of infrastructure.

Description

NVIDIA TensorRT is a comprehensive suite of APIs designed for efficient deep learning inference, which includes a runtime for inference and model optimization tools that ensure minimal latency and maximum throughput in production scenarios. Leveraging the CUDA parallel programming architecture, TensorRT enhances neural network models from all leading frameworks, adjusting them for reduced precision while maintaining high accuracy, and facilitating their deployment across a variety of platforms including hyperscale data centers, workstations, laptops, and edge devices. It utilizes advanced techniques like quantization, fusion of layers and tensors, and precise kernel tuning applicable to all NVIDIA GPU types, ranging from edge devices to powerful data centers. Additionally, the TensorRT ecosystem features TensorRT-LLM, an open-source library designed to accelerate and refine the inference capabilities of contemporary large language models on the NVIDIA AI platform, allowing developers to test and modify new LLMs efficiently through a user-friendly Python API. This innovative approach not only enhances performance but also encourages rapid experimentation and adaptation in the evolving landscape of AI applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

PyTorch
TensorFlow
CUDA
Dataoorts GPU Cloud
Hugging Face
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Broadcast
NVIDIA DRIVE
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA NIM
NVIDIA Riva Studio
NVIDIA virtual GPU
Python
RankGPT
RankLLM

Integrations

PyTorch
TensorFlow
CUDA
Dataoorts GPU Cloud
Hugging Face
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Broadcast
NVIDIA DRIVE
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA NIM
NVIDIA Riva Studio
NVIDIA virtual GPU
Python
RankGPT
RankLLM

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Exafunction

Website

exafunction.com

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/tensorrt

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Product Features

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Alternatives

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