Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
DeepGit provides a superior way to address the question "why is this code there?" compared to traditional Git clients by facilitating a thorough exploration of source code history. This innovative tool builds upon the git blame feature, enabling users to easily track modifications made to specific lines or segments of code. Notably, DeepGit excels in recognizing code movements, even when lines have undergone changes that render them non-identical. Furthermore, it is available for free, making it accessible for use in both personal and commercial settings. Users can seamlessly integrate DeepGit with various IDEs that support external tools, including popular platforms like Eclipse, Visual Studio, and IntelliJ IDEA, as well as robust text editors like Sublime. For those interested in mastering its functionalities, a tour is available to demonstrate how DeepGit operates effectively. Compatible with Windows, macOS, and Linux, DeepGit generates a blame report for the chosen file and conducts an analysis of the selected line and its surrounding context to trace its origin. It's important to note that the origin identified by DeepGit may not directly align with the corresponding left counterpart. Additionally, even when focusing on a single line, DeepGit often identifies a block of lines that serves as the best match for further investigation, enhancing the user's understanding of code evolution. This capability not only clarifies the rationale behind code changes but also aids developers in maintaining better code comprehension over time.
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.
API Access
Has API
No
API Access
Has API
No
Integrations
Eclipse IDE
Yes
PyTorch
No
Sublime Text
Yes
TensorFlow
No
Visual Studio
Yes
Integrations
Eclipse IDE
No
PyTorch
Yes
Sublime Text
No
TensorFlow
Yes
Visual Studio
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Syntevo
Country
Germany
Website
www.syntevo.com/deepgit/
Vendor Details
Company Name
Exafunction
Website
exafunction.com
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No