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Description
Dropbear is a compact SSH server and client that operates on various Unix-like platforms. It is an open-source program released under an MIT-style license, making it accessible for developers. Its design is particularly advantageous for "embedded" Linux systems, like those found in wireless routers. For those interested in staying updated on new releases or engaging in discussions, a low-traffic mailing list is available for subscriptions. With an efficient memory footprint, Dropbear can be compiled into a statically linked binary of just 110kB using uClibc on x86 architecture, provided that only the essential options are selected. Additionally, the server supports X11 forwarding and authentication-agent forwarding for clients using OpenSSH. Users can compile the server, client, key generator, and key converter into a single executable, similar to busybox, with the ability to disable certain features during compilation to conserve space. The software also includes a multi-hop mode that allows SSH TCP forwarding, enabling users to tunnel through multiple SSH hosts seamlessly in a single command, demonstrating its versatility in various networking scenarios. This flexibility makes Dropbear a favored choice for projects requiring lightweight and efficient SSH solutions.
Description
Luminal is a high-performance machine-learning framework designed with an emphasis on speed, simplicity, and composability, which utilizes static graphs and compiler-driven optimization to effectively manage complex neural networks. By transforming models into a set of minimal "primops"—comprising only 12 fundamental operations—Luminal can then implement compiler passes that swap these with optimized kernels tailored for specific devices, facilitating efficient execution across GPUs and other hardware. The framework incorporates modules, which serve as the foundational components of networks equipped with a standardized forward API, as well as the GraphTensor interface, allowing for typed tensors and graphs to be defined and executed at compile time. Maintaining a deliberately compact and modifiable core, Luminal encourages extensibility through the integration of external compilers that cater to various datatypes, devices, training methods, and quantization techniques. A quick-start guide is available to assist users in cloning the repository, constructing a simple "Hello World" model, or executing larger models like LLaMA 3 with GPU capabilities, thereby making it easier for developers to harness its potential. With its versatile design, Luminal stands out as a powerful tool for both novice and experienced practitioners in machine learning.
API Access
Has API
API Access
Has API
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
Matt Johnston
Country
Australia
Website
matt.ucc.asn.au/dropbear/dropbear.html
Vendor Details
Company Name
Luminal
Country
United States
Website
luminalai.com
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
