Get More From Accelerated Infrastructure on AWS
High-performance storage for AI and HPC that fits your AWS environment
Zoom out: See the features and benefits of running WEKA in the public cloud, across all providers
WEKA on Public CloudUSE CASES
Put Your AWS Compute to Work
Keep accelerated compute fed with the data performance it needs to stay productive as workloads and infrastructure scale.
AI Model Development
Keep GPU clusters fed with fast access to shared data across training, fine-tuning, checkpointing, and experimentation.
AI Inference
Feed production inference with fast access to data and context for long-context, agentic, and highly concurrent workloads.
High Performance Computing
Deliver throughput, IOPS, metadata performance, and low-latency shared access for highly parallel AWS workloads.
See What’s Possible on AWS
Real-world customer results and workload testing show the impact of WEKA® NeuralMesh™ across AI and HPC.
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GPU Utilization
Stability AI increased GPU utilization from 35% to 93% with NeuralMesh on AWS.
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Faster Experiments
Atomwise reduced experiments that took three months or more to less than one week with NeuralMesh on AWS.
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More Input Tokens
WEKA NeuralMesh Augmented Memory Grid™ served 3.6x more input tokens on the same AWS P6/B200 GPU footprint.
Trusted for AI and HPC on AWS
“We can now reach 93% GPU utilization when running our AI model training environment using WEKA on AWS.”
FEATURES
Upgrade Your Storage on AWS
Get more from the AWS infrastructure you've already chosen with storage built to work across your AWS environment.
High-Performance Data for AI
Give SageMaker HyperPod clusters fast access to the data they need for training, fine-tuning, and checkpointing. NeuralMesh scales storage performance with compute, so growing GPU clusters don't outpace the data infrastructure feeding them.
Scale Cloud AI Workloads Without Data Bottlenecks
Eliminate pipeline latency, maximize GPU utilization, and move data fluidly across your cloud environment with NeuralMesh.
Frequently Asked Questions
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