Give Hivly an idea. Get a finished social post. Add a photo and one sentence. Hivly writes the caption, designs the post, and schedules it for Facebook, Instagram, and LinkedIn.
sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Which is more popular?
Based on our record, CUDA Toolkit
seems to be a lot more popular than ShellNewHandler.
While we know about 42 links to CUDA Toolkit,
we've tracked only 2 mentions of ShellNewHandler.
social mentions
42 vs 2
Data Science And Machine Learning popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
Performance CUDA Toolkit provides highly optimized libraries and tools that enable developers to leverage NVIDIA GPUs to accelerate computation, vastly improving performance over traditional CPU-only applications.
Support for Parallel Programming CUDA offers extensive support for parallel programming, enabling developers to utilize thousands of threads, which is imperative for high-performance computing tasks.
Rich Development Ecosystem CUDA Toolkit integrates with popular programming languages and frameworks, such as Python, C++, and TensorFlow, allowing seamless development for AI, simulation, and scientific computing applications.
Comprehensive Libraries The toolkit includes a range of powerful libraries (like cuBLAS, cuFFT, and Thrust), which optimize common tasks in linear algebra, signal processing, and data analysis.
Scalability CUDA-enabled applications are highly scalable, allowing the same code to run on various NVIDIA GPUs, from consumer-grade to data center solutions, without code modifications.
Possible disadvantages
Hardware Dependency Developers need NVIDIA GPUs to utilize the CUDA Toolkit, making projects dependent on specific hardware solutions, which might not be feasible for all budgets or systems.
Learning Curve CUDA programming has a steep learning curve, especially for developers unfamiliar with parallel programming, which can initially hinder productivity and adoption.
Limited Multi-Platform Support CUDA is primarily developed for NVIDIA hardware, which means that applications targeting multiple platforms or vendor-neutral solutions might not benefit from using CUDA.
Complex Debugging Debugging CUDA applications can be complex due to the concurrent and parallel nature of the code, requiring specialized tools and a solid understanding of parallel computing.
Backward Compatibility Some updates in the CUDA Toolkit may affect backward compatibility, requiring developers to modify existing codebases when upgrading the CUDA version.
No features have been listed yet.
Analysis
An editorial look at what each product does well and who it suits.
CUDA ToolkitShellNewHandler
No analysis of CUDA Toolkit yet.
Overall verdict
ShellNewHandler is a niche, lightweight utility hosted on SourceForge designed to give users more control over the Windows 'New' context menu (the ShellNew menu). It can be considered good for its specific narrow use case, but it is an older, minimally maintained tool that may not suit all users, especially those on modern Windows versions.
Why this product is good
Provides direct control over customizing the Windows right-click 'New' menu, allowing users to add or remove file type entries
Lightweight and free, without bundled bloatware typical of some other free utilities
Simple and focused in scope, making it easy to understand for its specific purpose
Open distribution via SourceForge allows transparency and no-cost access
Recommended for
Power users who want to declutter or customize the Windows New context menu
IT administrators managing standardized desktop environments across multiple machines
Users comfortable with older utility-style tools and Windows registry-related tweaks
Not recommended for casual users seeking modern, actively supported software with regular updates
Videos
Walkthroughs and reviews on video.
CUDA Toolkit3 videos+ AddShellNewHandler0 videos+ Add
1971 Plymouth Cuda 440: Regular Car Reviews
More videos
-
Jackson Kayak Cuda Review
-
Great First Effort! The New $249 Signum Cuda
No ShellNewHandler videos yet. You could help us improve this page by suggesting one.
Category popularity
How often each product is chosen within a category, 0–100% relative to the other.
For contrast, we also built a no-limits version in PyTorch, using CUDA when it’s available. The network is straightforward -12 inputs, two hidden layers of 128 and 64 with ReLU, and 3 outputs for UP, HOLD, DOWN - so:
[12] → [128] →...
- Source: dev.to
/
about 1 year ago
Empowering Windows Developers: A Deep Dive into Microsoft and NVIDIA's AI Toolin
CUDA Toolkit Installation (Optional): If you plan to use CUDA directly, download and install the CUDA Toolkit from the NVIDIA Developer website: https://developer.nvidia.com/cuda-toolkit
Follow the installation instructions provided...
- Source: dev.to
/
over 1 year ago
Nvidia’s CUDA dominance is fading as developers embrace open-source alternatives like Triton and JAX, offering more flexibility, cross-hardware compatibility, and reducing reliance on proprietary software.
- Source: dev.to
/
over 1 year ago
I recently got libreoffice, but now the new option in right click looks like a mess. Can someone help me get rid of them please?
Use Shell New Handler. Run the portable app and simply untick the items you don't want to appear in your new context menu.
Source:
about 4 years ago
This menu should be easy to add/remove programs to... Who is really creating Access Databases from this menu often enough to keep it here? (Not me!) Is there an easy way to edit this?
I've always used ShellNewHandler for this. It's a really simple portable utility that allows you to remove most of the items from that menu. Tested it out on Windows 11 and it's still compatible.
Source:
over 5 years ago
Alternatives to CUDA Toolkit and ShellNewHandler
When comparing CUDA Toolkit and ShellNewHandler, you can also consider the following products.
TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Compare TensorFlow to CUDA Toolkit or ShellNewHandler:
TensorFlow
PyTorch
Keras
Scikit-learn
MLKit
Open Text Magellan
BAAR
