Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
ASReml-SA is a robust statistical software specifically tailored for mixed models that utilize Residual Maximum Likelihood (REML) for parameter estimation. Linear mixed-effects models serve as a versatile and comprehensive method for analyzing numerous datasets frequently encountered in fields such as animal, plant, and aquatic breeding, as well as in agriculture, environmental sciences, and medical research. The newest version, ASReml-SA 4.2, boasts three times the memory capacity of its predecessor 4.1, allowing for significantly larger analytical tasks to be performed. With enhancements in parallel processing and the capability to allocate memory for specific operations, the software has also seen improvements in speed; a comparison table is provided below to illustrate the speed enhancements realized across various analyses. ASReml-SA 4.2 not only accelerates processing but also offers users the potential for optimized performance tailored to their specific hardware and analytical needs. Ultimately, these advancements reflect ASReml-SA's commitment to facilitating efficient and effective data analysis.
Description
The RAPIDS software library suite, designed on CUDA-X AI, empowers users to run comprehensive data science and analytics workflows entirely on GPUs. It utilizes NVIDIA® CUDA® primitives for optimizing low-level computations while providing user-friendly Python interfaces that leverage GPU parallelism and high-speed memory access. Additionally, RAPIDS emphasizes essential data preparation processes tailored for analytics and data science, featuring a familiar DataFrame API that seamlessly integrates with various machine learning algorithms to enhance pipeline efficiency without incurring the usual serialization overhead. Moreover, it supports multi-node and multi-GPU setups, enabling significantly faster processing and training on considerably larger datasets. By incorporating RAPIDS, you can enhance your Python data science workflows with minimal code modifications and without the need to learn any new tools. This approach not only streamlines the model iteration process but also facilitates more frequent deployments, ultimately leading to improved machine learning model accuracy. As a result, RAPIDS significantly transforms the landscape of data science, making it more efficient and accessible.
API Access
Has API
No
API Access
Has API
No
Integrations
ActiveScale
Yes
Anaconda
No
Apache Spark
No
Capital One Spark Business Banking
No
Databricks
No
Domino Enterprise AI Platform
No
Gradient
No
HEAVY.AI
No
HPE Ezmeral Data Fabric
No
IBM Cloud
No
Integrations
ActiveScale
No
Anaconda
Yes
Apache Spark
Yes
Capital One Spark Business Banking
Yes
Databricks
Yes
Domino Enterprise AI Platform
Yes
Gradient
Yes
HEAVY.AI
Yes
HPE Ezmeral Data Fabric
Yes
IBM Cloud
Yes
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
No
Linux
No
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
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
VSN International
Founded
2000
Country
United Kingdom
Website
www.vsni.co.uk
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/rapids
Product Features
Statistical Analysis
Analytics
No
Association Discovery
Yes
Compliance Tracking
Yes
File Management
No
File Storage
Yes
Forecasting
No
Multivariate Analysis
No
Regression Analysis
No
Statistical Process Control
No
Statistical Simulation
Yes
Survival Analysis
No
Time Series
No
Visualization
No
Product Features
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No