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Description
Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.
Description
Distcc is a system designed for distributed compilation that speeds up the build process for C, C++, Objective-C, and Fortran by distributing compile tasks across various networked machines. This tool works effectively with both GCC and Clang toolchains, seamlessly intercepting compiler commands and redistributing them to remote daemons while maintaining optimization settings, include directories, and tracking of dependencies. The architecture is client-server based, featuring a lightweight listener that oversees job queues, prioritizes local compilation as necessary, and easily identifies available hosts through straightforward configuration or DNS. Additionally, Distcc accommodates cross-compilation setups, offers SSH tunneling for secure clusters, allows for the blacklisting of unreliable servers, and integrates well with modern build systems such as Make, CMake, and Ninja. It also includes monitoring tools that supply real-time data on job distribution and performance, and its compatibility with compilation databases (compdb) permits detailed management of distributed workloads. Overall, Distcc is a powerful solution that significantly enhances build efficiency across diverse development environments.
API Access
Has API
API Access
Has API
Integrations
3LC
C
C++
Coiled
Dash
Flower
Gensim
JAX
MPI for Python (mpi4py)
Make
Integrations
3LC
C
C++
Coiled
Dash
Flower
Gensim
JAX
MPI for Python (mpi4py)
Make
Pricing Details
Free
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
NumPy
Website
numpy.org
Vendor Details
Company Name
distcc
Founded
2002
Country
United States
Website
www.distcc.org
Product Features
Product Features
Build Automation
Automated Testing
Build Cache
Build Management Tools
Build Metrics
Change Only Compiling
Debugging Tools
Dependency Management
IDE Compatibility
Parallel Testing
Plugin Library
Source Code Management
Version Conflict Resolution
