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Make Multi-GPU Cloud AI a Reality

If you’re building large-scale AI, you’re already multi-cloud by choice (to avoid lock-in) or by necessity (to access scarce GPU capacity). Teams frequently chase capacity bursts, “we need 1,000 GPUs for eight weeks,” across whichever regions or providers can deliver. What slows you down isn’t GPUs, it’s data. Simply accessing the data needed to train, deploy, and serve AI models at the speed and scale required – wherever AI workloads and GPUs are deployed – is in fact not simple at all. In this article, learn how Alluxio brings Simplicity, Speed, and Scale to Multi-GPU Cloud deployments.

Accelerate your Cloud Object Storage for AI Workloads

Turn your existing S3 storage into an AI-ready storage layer with sub-ms latency and terabytes per second throughout per Alluxio cluster with linear scalability — no data migration required.

Alluxio's Strong Q2: Sub-Millisecond AI Latency, 50%+ Customer Growth, and Industry-Leading MLPerf Results

Alluxio's strong Q2 featured Enterprise AI 3.7 launch with sub-millisecond latency (45× faster than S3 Standard), 50%+ customer growth including Salesforce and Geely, and MLPerf Storage v2.0 results showing 99%+ GPU utilization, positioning the company as a leader in maximizing AI infrastructure ROI.

AI Infra Day Sessions Recap

Alluxio, the data platform company for all data-driven workloads, hosted the community event “AI Infra Day” on October 25, 2023. This virtual event brought together technology leaders working on AI infrastructure from Uber, Meta, and Intel, to delve into the intricate aspects of building scalable, performant, and cost-effective AI platforms.

The Data-Driven Heartbeat of Artificial Intelligence

This article was initially posted on Solutions Review.

Artificial Intelligence (AI) has consistently been in the limelight as the precursor of the next technological era. Its limitless applications, ranging from simple chatbots to intricate neural networks capable of deep learning, promise a future where machines understand and replicate complex human processes. Yet, at the heart of this technological marvel is something foundational yet often overlooked: data.

GPUs Are Fast, I/O is Your Bottleneck

This article was initially posted on ITOpsTimes.

Unless you’ve been living off the grid, the hype around Generative AI has been impossible to ignore. A critical component fueling this AI revolution is the underlying computing power, GPUs. The lightning-fast GPUs enable speedy model training. But a hidden bottleneck can severely limit their potential – I/O. If data can’t make its way to the GPU fast enough to keep up with its computations, those precious GPU cycles end up wasted waiting around for something to do. This is why we need to bring more awareness to the challenges of I/O bottlenecks.