GlobeNewswire | October 19, 2023
Alluxio, the data platform company for all data-driven workloads, today introduced Alluxio Enterprise AI, a new high-performance data platform designed to meet the rising demands of Artificial Intelligence (AI) and machine learning (ML) workloads on an enterprise’s data infrastructure. Alluxio Enterprise AI brings together performance, data accessibility, scalability and cost-efficiency to enterprise AI and analytics infrastructure to fuel next-generation data-intensive applications like generative AI, computer vision, natural language processing, large language models and high-performance data analytics.
To stay competitive and achieve stronger business outcomes, enterprises are in a race to modernize their data and AI infrastructure. On this journey, they find that legacy data infrastructure cannot keep pace with next-generation data-intensive AI workloads. Challenges around low performance, data accessibility, GPU scarcity, complex data engineering, and underutilized resources frequently hinder enterprises' ability to extract value from their AI initiatives. According to Gartner®, “the value of operationalized AI lies in the ability to rapidly develop, deploy, adapt and maintain AI across different environments in the enterprise. Given the engineering complexity and the demand for faster time to market, it is critical to develop less rigid AI engineering pipelines or build AI models that can self-adapt in production.” “By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%.”
Alluxio empowers the world’s leading organizations with the most modern Data & AI platforms, and today we take another significant leap forward, said Haoyuan Li, Founder and CEO, Alluxio. Alluxio Enterprise AI provides customers with streamlined solutions for AI and more by enabling enterprises to accelerate AI workloads and maximize value from their data. The leaders of tomorrow will know how to harness transformative AI and become increasingly data-driven with the newest technology for building and maintaining AI infrastructure for performance, seamless access and ease of management.
With this announcement, Alluxio expands from a one-product portfolio to two product offerings - Alluxio Enterprise AI and Alluxio Enterprise Data - catering to the diverse needs of analytics and AI. Alluxio Enterprise AI is a new product that builds on the years of distributed systems experience accumulated from the previous Alluxio Enterprise Editions, combined with a new architecture that is optimized for AI/ML workloads. Alluxio Enterprise Data is the next-gen version of Alluxio Enterprise Edition, and will continue to be the ideal choice for businesses focused primarily on analytic workloads.
Accelerating End-to-End Machine Learning Pipeline
Alluxio Enterprise AI enables enterprise AI infrastructure to be performant, seamless, scalable and cost-effective on existing data lakes. Alluxio Enterprise AI helps data and AI leaders and practitioners achieve four key objectives in their AI initiatives: high-performance model training and deployment to yield quick business results; seamless data access for workloads across regions and clouds; infinite scale that has been battle-tested at internet giant’s scale; and maximized return on investments by working with existing tech stack instead of costly specialized storage. With Alluxio Enterprise AI, enterprises can expect up to 20x faster training speed compared to commodity storage, up to 10x accelerated model serving, over 90% GPU utilization, and up to 90% lower costs for AI infrastructure.
Alluxio Enterprise AI has a distributed system architecture with decentralized metadata to eliminate bottlenecks when accessing massive numbers of small files, typical of AI workloads. This provides unlimited scalability beyond legacy architectures, regardless of file size or quantity. The distributed cache is tailored to AI workload I/O patterns, unlike traditional analytics. Finally, it supports analytics and full machine learning pipelines - from ingestion to ETL, pre-processing, training and serving.
Alluxio Enterprise AI includes the following key features:
Epic Performance for Model Training and Model Serving - Alluxio Enterprise AI offers significant performance improvements to model training and serving on an enterprise’s existing data lakes. The enhanced set of APIs for model training can deliver up to 20x performance over commodity storage. For model serving, Alluxio provides extreme concurrency and up to 10x acceleration for serving models from offline training clusters for online inference.
Intelligent Distributed Caching Tailored to I/O Patterns of AI Workloads - Alluxio Enterprise AI’s distributed caching feature enables AI engines to read and write data through the high performance Alluxio cache instead of slow data lake storage. Alluxio’s intelligent caching strategies are tailored to the I/O patterns of AI engines – large file sequential access, large file random access, and massive small file access. This optimization delivers high throughput and low latency for data-hungry GPUs. Training clusters are continuously fed data from the high-performance distributed cache, achieving over 90% GPU utilization.
Seamless Data Access for AI Workloads Across On-prem and Cloud Environments - Alluxio Enterprise AI provides a single pane of glass for enterprises to manage AI workloads across diverse infrastructure environments easily. Providing a source of truth of data for the machine learning pipeline, the product fundamentally removes the bottleneck of data lake silos in large enterprises. Sharing data between different business units and geographical locations becomes seamless with a standard data access layer via the Alluxio Enterprise AI platform.
New Distributed System Architecture, Battle-tested At Scale - Alluxio Enterprise AI builds on a new innovative decentralized architecture, DORA (Decentralized Object Repository Architecture). This architecture sets the foundation to provide infinite scale for AI workloads. It allows an AI platform to handle up to 100 billion objects with commodity storage like Amazon S3. Leveraging Alluxio’s proven expertise in distributed systems, this new architecture has addressed the ever-increasing challenges of system scalability, metadata management, high availability, and performance.
“Performance, cost optimization and GPU utilization are critical for optimizing next-generation workloads as organizations seek to scale AI throughout their businesses,” said Mike Leone, Analyst, Enterprise Strategy Group. “Alluxio has a compelling offering that can truly help data and AI teams achieve higher performance, seamless data access, and ease of management for model training and model serving.”
“We've collaborated closely with Alluxio and consider their platform essential to our data infrastructure,” said Rob Collins, Analytics Cloud Engineering Director, Aunalytics. “Aunalytics is enthusiastic about Alluxio's new distributed system for Enterprise AI, recognizing its immense potential in the ever-evolving AI industry.”
“Our in-house-trained large language model powers our Q&A application and recommendation engines, greatly enhancing user experience and engagement,” said Mengyu Hu, Software Engineer in the data platform team, Zhihu. “In our AI infrastructure, Alluxio is at the core and center. Using Alluxio as the data access layer, we’ve significantly enhanced model training performance by 3x and deployment by 10x with GPU utilization doubled. We are excited about Alluxio’s Enterprise AI and its new DORA architecture supporting access to massive small files. This offering gives us confidence in supporting AI applications facing the upcoming artificial intelligence wave.”
Deploying Alluxio in Machine Learning Pipelines
According to Gartner, data accessibility and data volume/complexity is one the top three barriers to the implementation of AI techniques within an organization. Alluxio Enterprise AI can be added to the existing AI infrastructure consisting of AI compute engines and data lake storage. Sitting in the middle of compute and storage, Alluxio can work across model training and model serving in the machine learning pipeline to achieve optimal speed and cost. For example, using PyTorch as the engine for training and serving, and Amazon S3 as the existing data lake:
Model Training: When a user is training models, the PyTorch data loader loads datasets from a virtual local path /mnt/alluxio_fuse/training_datasets. Instead of loading directly from S3, the data loader will load from the Alluxio cache instead. During training, the cached datasets will be used in multiple epochs, so the entire training speed is no longer bottlenecked by retrieving from S3. In this way, Alluxio speeds up training by shortening data loading and eliminates GPU idle time, increasing GPU utilization. After the models are trained, PyTorch writes the model files to S3 through Alluxio.
Model Serving: The latest trained models need to be deployed to the inference cluster. Multiple TorchServe instances read the model files concurrently from S3. Alluxio caches these latest model files from S3 and serves them to inference clusters with low latency. As a result, downstream AI applications can start inferencing using the most up-to-date models as soon as they are available.
Platform Integration with Existing Systems
To integrate Alluxio with the existing platform, users can deploy an Alluxio cluster between compute engines and storage systems. On the compute engine side, Alluxio integrates seamlessly with popular machine learning frameworks like PyTorch, Apache Spark, TensorFlow and Ray. Enterprises can integrate Alluxio with these compute frameworks via REST API, POSIX API or S3 API.
On the storage side, Alluxio connects with all types of filesystems or object storage in any location, whether on-premises, in the cloud, or both. Supported storage systems include Amazon S3, Google GCS, Azure Blob Storage, MinIO, Ceph, HDFS, and more.
Alluxio works on both on-premise and cloud, either bare-metal or containerized environments. Supported cloud platforms include AWS, GCP and Azure Cloud.
PR Newswire | January 25, 2024
dxFeed, a global leader in data solutions and index management for the financial industry, announces the launch of an Infrastructure as a Service (IaaS) project for Tradu, an advanced multi-asset trading platform catering to active traders and investors. In this venture, dxFeed manages the crucial aspects of infrastructure and data provision for Tradu.
As an award-winning IaaS provider (the Best Infrastructure Provider by the Sell-Side Technology Awards 2023), dxFeed is poised to address all technical challenges related to market data delivery to hundreds of thousands of end users, allowing Tradu to focus on its core business objectives. Users worldwide can seamlessly connect to Tradu's platform, receiving authorization tokens for access to high-quality market data from the EU, US, Hong Kong, and Australian Exchanges. This approach eliminates the complexities and bottlenecks associated with building, maintaining, and scaling the infrastructure required for such extensive global data access.
dxFeed's scalable low latency infrastructure ensures the delivery of consolidated and top-notch market data from diverse sources to the clients located in Asia, Americas and Europe. With the ability to rapidly reconfigure and accommodate the growing performance demands, dxFeed is equipped to serve hundreds of thousands of concurrent clients, with the potential to scale the solution even further in order to meet the constantly growing demand, at the same time providing a seamless and reliable experience.
One of the highlights of this collaboration is the introduction of brand-new data feed services exclusively for Tradu's Stocks platform. This proprietary solution enhances Tradu's offerings and demonstrates dxFeed's commitment to delivering tailored and innovative solutions.
Tradu also benefits from dxFeed's Stocks Radar—a comprehensive technical and fundamental market analysis solution. This Software as a Service (SaaS) seamlessly integrates with infrastructure, offering added value to traders and investors by simplifying complex analytical tasks.
Moreover, Tradu leverages the advantages of dxFeed's composite feed (the winner at The Technical Analyst Awards). This accolade reinforces dxFeed's commitment to delivering excellence in data provision, further solidifying Tradu's position as a global leader in online foreign exchange.
"When we were thinking of our new sophisticated multi-asset trading platform for the active trader and investors we met with the necessity of expanding instrument and user numbers. We realized we needed a highly competent, professional team to deploy the infrastructure, taking into account the peculiarities of our processes and services," said Brendan Callan, CEO of Tradu. "On the one hand, it allows our clients to receive quality consolidating data from multiple sources. On the other hand, as a leading global provider of online foreign exchange, we can dispose of dxFeed's geo-scalable infrastructure and perform rapid reconfiguration to meet growing performance demands to provide data to hundreds of thousands of our clients around the globe."
"The range of businesses finding the Market Data IaaS (Infrastructure as a Service) model appealing continues to expand. This approach is gaining traction among various enterprises, from agile startups seeking rapid development to established, prominent brands acknowledging the strategic benefits of delegating market data infrastructure to specialized firms," said Oleg Solodukhin, CEO of dxFeed.
By taking on the responsibilities of infrastructure and data provision, dxFeed empowers Tradu to focus on innovation and client satisfaction, setting the stage for a transformative journey in the dynamic world of financial trading.
dxFeed is a leading market data and services provider and calculation agent for the capital markets industry. According to the WatersTechnology 2022 IMD & IRD awards honors, it's the "Most Innovative Market Data Project." dxFeed focuses primarily on delivering financial information and services to buy- and sell-side institutions in global markets, both traditional and crypto. That includes brokerages, prop traders, exchanges, individuals (traders, quants, and portfolio managers), and academia (educational institutions and researchers).
Follow us on Twitter, Facebook, and LinkedIn.
Contact dxFeed: email@example.com
Tradu is headquartered in London with offices around the world. The global Tradu team speaks more than two dozen languages and prides itself on its responsive and helpful client support.
Stratos also operates FXCM, an FX and CFD platform founded in 1999. Stratos will continue to offer FXCM services alongside Tradu's multi-asset platform.
IT Systems Management
PR Newswire | January 16, 2024
The Internet Corporation for Assigned Names and Numbers (ICANN), the nonprofit organization that coordinates the Domain Name System (DNS), announced today the ICANN Grant Program, which will make millions of dollars in funding available to develop projects that support the growth of a single, open and globally interoperable Internet. ICANN is opening an application cycle for the first $10 million in grants in March 2024.
Internet connectivity continues to increase worldwide, particularly in developing countries. According to the International Telecommunication Union (ITU), an estimated 5.3 billion of the world's population use the Internet as of 2022, a growth rate of 6.1% over 2021. The Grant Program will support this next phase of global Internet growth by fostering an inclusive and transparent approach to developing stable, secure Internet infrastructure solutions that support the Internet's unique identifier systems.
"With the rapid evolution of emerging technologies, businesses and security models, it is critical that the Internet's unique identifier systems continue to evolve," said Sally Costerton, Interim President and CEO, ICANN. "The ICANN Grant Program offers a new avenue to further those efforts by investing in projects that are committed to and support ICANN's vision of a single, open and globally interoperable Internet that fosters inclusion amongst a broad, global community of users."
ICANN expects to begin accepting grant applications on 25 March 2024. The application window will remain open until 24 May 2024. A complete list of eligibility criteria can be found at: https://icann.org/grant-program.
Once the application window closes, all applications are subject to admissibility and eligibility checks. An Independent Application Assessment Panel will review admissible and eligible applications and the tentative timeline to announce the grantees of the first cycle is in January of 2025.
Potential applicants will have several opportunities to learn more about the Call for Proposals and ask ICANN Grant Program staff members questions through question-and-answer webinar sessions in the coming months. For more information on the program, including eligibility and submission requirements, the ICANN Grant Program Applicant Guide is available at
ICANN's mission is to help ensure a stable, secured and unified global Internet. To reach another person on the Internet, you need to type an address – a name or a number – into your computer or other device. That address must be unique so computers know where to find each other. ICANN helps coordinate and support these unique identifiers across the world.