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What is Tencent Cloud Load Balancer?

A cluster of CLB consists of four physical servers, achieving an impressive availability rate of up to 99.95%. Even when only one CLB instance remains functional, it can manage over 30 million simultaneous connections. The architecture is designed to quickly identify and remove any malfunctioning instances while keeping healthy ones operational, ensuring that the backend servers function continuously. Furthermore, the CLB cluster allows for flexible scaling of application service capacity based on business needs, automatically creating and terminating CVM instances through the Auto Scaling dynamic scaling group. In addition to these features, there is a robust dynamic monitoring system paired with a billing mechanism that tracks resource usage to the second, eliminating the necessity for manual resource management or forecasting. This efficient approach not only enhances resource allocation but also significantly minimizes waste, enabling businesses to concentrate on their growth instead of managing infrastructure. The integration of these sophisticated features fosters a more agile and efficient computing environment, ultimately leading to greater operational success.

What is Exafunction?

Exafunction significantly boosts the effectiveness of your deep learning inference operations, enabling up to a tenfold increase in resource utilization and savings on costs. This enhancement allows developers to focus on building their deep learning applications without the burden of managing clusters and optimizing performance. Often, deep learning tasks face limitations in CPU, I/O, and network capabilities that restrict the full potential of GPU resources. However, with Exafunction, GPU code is seamlessly transferred to high-utilization remote resources like economical spot instances, while the main logic runs on a budget-friendly CPU instance. Its effectiveness is demonstrated in challenging applications, such as large-scale simulations for autonomous vehicles, where Exafunction adeptly manages complex custom models, ensures numerical integrity, and coordinates thousands of GPUs in operation concurrently. It works seamlessly with top deep learning frameworks and inference runtimes, providing assurance that models and their dependencies, including any custom operators, are carefully versioned to guarantee reliable outcomes. This thorough approach not only boosts performance but also streamlines the deployment process, empowering developers to prioritize innovation over infrastructure management. Additionally, Exafunction’s ability to adapt to the latest technological advancements ensures that your applications stay on the cutting edge of deep learning capabilities.

Media

Media

Integrations Supported

PyTorch
Tencent Cloud
TensorFlow

Integrations Supported

PyTorch
Tencent Cloud
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Tencent

Date Founded

2013

Company Location

China

Company Website

intl.cloud.tencent.com/product/clb

Company Facts

Organization Name

Exafunction

Company Website

exafunction.com

Categories and Features

Load Balancing

Authentication
Automatic Configuration
Content Caching
Content Routing
Data Compression
Health Monitoring
Predefined Protocols
Redundancy Checking
Reverse Proxy
SSL Offload
Schedulers

Categories and Features

Deep Learning

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

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