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Meet FlashBlade//EXA. More AI. Less Waiting.

Meet FlashBlade//EXA: AI storage that scales effortlessly. More AI. Less waiting. No bottlenecks. No limits. Just performance.
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00:00
Traditional parallel file systems struggle to keep up with evolving AI workloads. These are built for static sequential processes, not highly dynamic multi-modal data streams. And as AI models grow larger and workloads become more complex, these legacy systems create performance bottlenecks, add unnecessary complexity, and limit scalability.
00:22
This results in slower innovation underutilized GPUs and wasted investment. To truly unlock AI's potential, you need a storage solution that scales as fast as your workloads. Enter Flash Blade Xa. AI is transforming every industry from transportation to medical breakthroughs. While the world is captivated by AI's possibilities, behind the scenes,
00:52
a massive challenge is emerging. The demand and newfound use cases in AI and high performance computing to feed powerful and expensive GPUs are evolving faster than most storage infrastructure can keep up. Models are expanding, generating unprecedented volumes of data across training, testing, tuning, and inference workflows. Yet many AI teams still rely on legacy
01:19
parallel file systems that weren't built for the scale. Flash Bla Xa, however, is different. Designed for large scale AI and high performance computing, it removes the limitations that slow innovation. In fact, it accelerates it.
01:36
And while traditional parallel file systems require complex setup and ongoing tuning, Flash Bla Xa is built for simplicity. It deploys seamlessly in extreme performance large scale AI environments and integrates effortlessly with existing networks, eliminating the need for multiple network segments. This means simplified operations,
01:59
reduced complexity, and faster time to AI insights. But performance isn't just about speed, it's also about flexibility. Unlike other solutions, Flash Blade Xa supports any compute cluster and is optimized for the latest AI infrastructure, ensuring maximum performance no matter how your AI or high performance compute environment evolves. Flash Blade Xa removes the bottlenecks of
02:25
legacy storage systems by separating the metadata core from the data nodes. If your AI pipelines are slowing you down, scaling your metadata nodes ensures high concurrency workloads run at full speed, handling billions of operations per second. Need more capacity or throughput. Expanding data nodes supports massive AI data sets and can deliver 10 terabytes per second or
02:49
more of read performance for training, inference, and real-time AI analytics. But what does this look like in practice? Let's say you've just deployed your first flash blade XA and want to benchmark its performance for AI and HPC workloads. To do that, we'll run two synthetic tests, FIO read and FIO write.
03:10
These benchmarks simulate the heavy read and write demands under intense AI and HPC workloads. The horsepower we're dealing with here is a single flash blade XA metadata node and 25 data nodes. This is already a great starting point that we can scale out later. As this process runs, we're monitoring in real time.
03:32
Traditional storage would buckle under these workloads, but Flashblade Xa processes massive metadata operations at peak efficiency. For rights we achieved over 1 terabyte per second and for reads we hit over 2 terabytes a second, impressive numbers. These speeds mean AI teams can ingest massive training data sets faster, perform asynchronous checkpointing at unmatched speeds,
03:57
and accelerate the overall end to end AI workflow, avoiding any GPU idle time. To understand what's happening, let's take a deeper look at system performance. Flash Bla Xa integrates seamlessly with Prometheus and Grafita, allowing AI teams to correlate storage performance with workload demands in real time. Here we can see that each of the data nodes are hitting 100% CPU utilization from two Mellanox
04:23
network cards on Gen 4 PCI slots pushing balanced IO bandwidth through each port, and that's with 25 data nodes and one flash blade XA metadata node. This confirms that in this test, data node CPU and IO bandwidth over the Geno PCI slots is the limiting factor, not the metadata node. Grafina also shows that our data nodes are using RDMA over NFS in the two network ports.
04:50
The NFSD dashboard provides the aggregated throughput at the protocol stack, which equals the sum of the bandwidth reported through the two Mellanox cards. This confirms zero packet loss, meaning the network is non-blocking and is running at full efficiency, and this is with 25 data nodes. If we scale Flash Blade XA to over 100 data nodes, it can achieve the best read performance
05:14
of over 10 terabytes per second, and if we scale for rights, Flash Blade Xa can deliver the best right performance of over 5 terabytes per second. This demonstrates the linear predictable scalability of reads and writes with Flash Blade XF. Flash Blade Xa supports billions of metadata operations per 2nd and 20 times the file systems in a single name space compared to
05:37
traditional solutions. This means faster AI training, testing, and inference along with more efficient asynchronous checkpointing and breakthroughs in retrieval augmented generation and multimodal AI workloads, no matter how complex the model. And with faster access to your data, you're maximizing your investment in GPU and compute
05:59
resources so they stay fully utilized and not sitting idle waiting for storage. Flash Blade Xa isn't just ready for today, it's built for what's next. So today you're training billion parameter models. Tomorrow you might be processing 1 trillion parameter multimodal workloads we haven't even imagined yet. But one thing is certain AI isn't slowing down
06:22
and neither should your infrastructure. Flashblate access scales with you, whether you're running an AI factory, accelerating inference, or preparing for the next wave of innovation. With Flash Blade Xa, you can be sure storage will never be a bottleneck again. So see how Flash Blade Xcel performs with your AI workloads.
06:43
Reach out to Pure Storage to benchmark it with your data today. And if you want to see more ways Pure Storage is helping organizations work smarter, check out Pure 360. It's your hub for quick overviews, expert led walkthroughs, and interactive demos all designed to simplify your infrastructure and help you achieve more.
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Cost-efficient storage for Azure, AWS, and private clouds

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Databases
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Key benefits:

  • Instant, space-efficient snapshots

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AI/ML and analytics
Training, inference, data lakes, HPC

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  • Predictable throughput for faster training and ingest

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