Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

WekaIO Introduces Weka AI to Enable Accelerated Edge to Core to Cloud Data Pipelines

Expedites Time-To-Market and To-Value While Delivering Agility and Security at Scale

WekaIO, the innovation leader in high-performance and scalable file storage, and a NVIDIA Partner Network Solution Advisor, today introduced Weka AI, a transformative storage solution framework underpinned by the Weka File System (WekaFS™) that enables accelerated edge to core to cloud data pipelines. Weka AI is a framework of customizable reference architectures (RAs) and software development kits (SDKs) with leading technology alliances like NVIDIA, Mellanox and others in the Weka Innovation Network (WIN™). Weka AI enables chief data officers, data scientists and data engineers to accelerate genomics, medical imaging, financial services industry (FSI) and advanced driver-assistance systems (ADAS) deep learning (DL) pipelines and is available to easily scale from small to medium and large integrated solutions, through resellers and channel partners.

“The DevOps culture transformed the agility in code development, and a similar culture is required on the data side as well. Therefore, creating a DataOps culture has become a critical discipline for any organization that wants to have a competitive edge and survive in this data-driven market.”

Artificial Intelligence (AI) data pipelines are inherently different from traditional file-based WekaIO applications. Each stage within AI data pipelines has distinct storage IO requirements: massive bandwidth for ingest and training, mixed read/write handling for extract, transform, load (ETL), ultra-low latency for inference, and a single namespace for entire data pipeline visibility. Additionally, AI at the edge is driving the need for edge to core to cloud data pipelines. Hence, the solution must meet all these varied requirements, and deliver timely insights at scale. Traditional solutions lack these capabilities and often fall short in meeting performance, shareability across personas and data mobility requirements. Industries demand solutions to overcome those challenges─they demand data management for the AI Era, which provides actionable intelligence by breaking silos, providing operational agility and governance to these data pipelines.

Recommended AI News: Nokia Publishes People & Planet Report 2019 As It Looks To Keep People Connected Through The Pandemic

Weka AI is a framework combining multiple technology partnerships, architected to accelerate DataOps, by solving the storage challenges common with IO-intensive workloads, like AI, and deliver production-ready solutions. It leverages WekaFS to accelerate the AI data pipeline, delivering more than 73 GB/sec of bandwidth to a single GPU client. In addition, it delivers operational agility with versioning, explainability and reproducibility and provides governance and compliance with in-line encryption and data protection. Engineered solutions with partners in the WIN program ensures Weka AI will provide data collection, workspaces and deep neural network (DNN) training, simulation, inference and lifecycle management for the entire data pipeline.

Recommended AI News: COVID-19 Makes Mobile Operators, AI And Analytics As Critical As Hand Sanitizer

Related Posts
1 of 20,125

Supporting Quotes

Kevin Tubbs, Senior Director, Technology and Business Development, Advanced Solutions Group, Penguin Computing
“Weka AI provides a solution to meet the requirements of modern AI applications. We are very excited to be working with Weka to accelerate next generation AI data pipelines.”

Amrinderpal Singh Oberai, Director, Data & AI, Groupware Technology
“The Groupware Data & AI team has tested and validated the Weka AI reference architecture in-house. The Weka AI framework provides us the flexibility and technology innovation to build custom solutions along with other ISV technology partners to solve industry challenges through AI.”

Paresh Kharya, Director of Product Management for Accelerated Computing, NVIDIA
“End-to-end application performance for AI requires feeding high performance NVIDIA GPUs with a high throughput data pipeline. Weka AI leverages GPUDirect storage to provide a direct path between storage and GPUs, eliminating I/O bottlenecks for data intensive AI applications.”

Gilad Shainer, Senior Vice President Marketing, Mellanox Technologies
“InfiniBand has become the de-facto standard for high performance and scalable AI infrastructures, delivering high data throughout and In-Network Computing acceleration engines. Utilizing GPUDirect and GPUDirect storage over InfiniBand with the Weka AI framework, provides our mutual customers with a world-leading platform for AI applications.”

Liran Zvibel, CEO and Co-Founder, WekaIO
“GPUDirect Storage eliminates IO bottlenecks and dramatically reduces latency, delivering full bandwidth to data hungry applications. By supporting GPUDirect Storage in its implementations, Weka AI continues to deliver on its promise of highest performance at any scale for the most data-intensive applications.”

Shailesh Manjrekar, Head of AI and Strategic Alliances, WekaIO
“We are very excited to launch Weka AI to help businesses embark on their digital transformation journey. Line-of-business users as well as IT leaders can now implement AI 2.0 and cognitive computing workflows that scale, accelerate and derive actionable business insights, thus enabling Accelerated DataOps.”

Recommended AI News: AI: Increasing The Intelligence On Smartphones

Leave A Reply

Your email address will not be published.