DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports Events Over 2 million developers have joined DZone. Join Today! Thanks for visiting DZone today,
Edit Profile Manage Email Subscriptions Moderation Admin Console How to Post to DZone Article Submission Guidelines
View Profile
Sign Out
Refcards
Trend Reports
Events
Zones
Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
  1. DZone
  2. Data Engineering
  3. AI/ML
  4. GPU Open Analytics Initiative

GPU Open Analytics Initiative

Continuum Analytics, H2O.ai, and MapD Technologies announced that they will be creating open common data frameworks for GPU in-memory analytics.

Tom Smith user avatar by
Tom Smith
CORE ·
May. 09, 17 · News
Like (1)
Save
Tweet
Share
4.35K Views

Join the DZone community and get the full member experience.

Join For Free

Continuum Analytics, H2O.ai, and MapD Technologies have formed the GPU Open Analytics Initiative (GOAI) to create common data frameworks enabling developers and statistical researchers to accelerate data science on GPUs. GOAI will foster the development of a data science ecosystem on GPUs by allowing resident applications to interchange data seamlessly and efficiently. BlazingDB, Graphistry, and Gunrock from UC Davis led by CUDA Fellow John Owens have joined the founding members to contribute their technical expertise.

The formation of the Initiative comes at a time when analytics and Machine Learning workloads are increasingly being migrated to GPUs. However, while individually powerful, these workloads have not been able to benefit from the power of end-to-end GPU computing. A common standard will enable intercommunication between the different data applications and speed up the entire workflow, removing latency and decreasing the complexity of data flows between core analytical applications. 

At the GPU Technology Conference (GTC), NVIDIA’s annual GPU developers’ conference, the Initiative announced its first project: an open-source GPU Data Frame with a corresponding Python API. The GPU Data Frame is a common API that enables the efficient interchange of data between processes running on the GPU. End-to-end computation on the GPU avoids transfers back to the CPU or copying of in-memory data reducing compute time and cost for high-performance analytics common in artificial intelligence workloads.

Users of the MapD Core database can output the results of a SQL query into the GPU Data Frame, which then can be manipulated by the Continuum Analytics’ Anaconda NumPy-like Python API or used as input into the H2O suite of machine learning algorithms without additional data manipulation. In early internal tests, this approach exhibited order-of-magnitude improvements in processing times compared to passing the data between applications on a CPU. 

“The data science and analytics communities are rapidly adopting GPU computing for Machine Learning and deep learning. However, CPU-based systems still handle tasks like subsetting and preprocessing training data, which creates a significant bottleneck,” says Todd Mostak, CEO and co-founder of MapD Technologies. “The GPU Data Frame makes it easy to run everything from ingestion to preprocessing to training and visualization directly on the GPU. This efficient data interchange will improve performance, encouraging the development of ever more sophisticated GPU-based applications.” 

“GPU Data Frame relies on the Anaconda platform as the foundational fabric that brings data science technologies together to take full advantage of GPU performance gains,” says Travis Oliphant, co-founder and chief data scientist of Continuum Analytics. “Using NVIDIA’s technology, Anaconda is mobilizing the Open Data Science movement by helping teams avoid the data transfer process between CPUs and GPUs and move nimbly toward their larger business goals. The key to producing this kind of innovation are great partners like H2O and MapD.”

“Truly diverse open-source ecosystems are essential for adoption — we are excited to start GOAI for GPUs alongside leaders in data and analytics pipeline to help standardize data formats,” says Sri Ambati, CEO and co-founder of H2O.ai. “GOAI is a call for the community of data developers and researchers to join the movement to speed up analytics and GPU adoption in the enterprise.”

The GPU Open Analytics Initiative is actively welcoming participants who are committed to open source and to GPUs as a computing platform.

Details of the GPU Data Frame can be found at the Initiative’s GitHub.

Data science Analytics Initiative Machine learning Open source

Opinions expressed by DZone contributors are their own.

Popular on DZone

  • Top Five Tools for AI-based Test Automation
  • Tech Layoffs [Comic]
  • Better Performance and Security by Monitoring Logs, Metrics, and More
  • DevOps Roadmap for 2022

Comments

Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 600 Park Offices Drive
  • Suite 300
  • Durham, NC 27709
  • support@dzone.com
  • +1 (919) 678-0300

Let's be friends: