Audience
Businesses looking for a GPU cloud solution for deep learning
About GPUEater
Persistence container technology enables lightweight operation. Pay-per-use in seconds rather than hours or months. Fees will be paid by credit card in the next month. High performance, but low price compared to others. Will be installed in the world's fastest supercomputer by Oak Ridge National Laboratory. Machine learning applications like deep learning, computational fluid dynamics, video encoding, 3D graphics workstation, 3D rendering, VFX, computational finance, seismic analysis, molecular modeling, genomics, and other server-side GPU computation workloads.
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Charg
Charg is an AI infrastructure lifecycle platform that transforms proven enterprise-grade supercomputing systems into scalable AI and high-performance computing cloud environments. Its public HPC cloud provides access to anything from a single GPU to a full 60+ PFLOPS cluster, giving teams supercomputing power without owning or managing the underlying hardware. It redeploys hyperscaler-class CRAY supercomputers and mature NVIDIA DGX architecture, combining clustered NVIDIA V100 GPUs with 200 GbE InfiniBand networking and petabytes of high-density all-flash CEPH storage for low-latency, high-throughput performance. Charg is built for demanding AI, scientific research, and engineering workloads, including model training, scaled inference, simulations, advanced data analysis, finite element analysis, and computational fluid dynamics. Its API-driven infrastructure scales with existing workflows and supports on-demand capacity without the operational restrictions.
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GenomeBrowse
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GPUonCLOUD
Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.
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Pricing
Starting Price:
$0.0992 per hour
Integrations
Company Information
GPUEater
United States
gpueater.com
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Product Details
Platforms Supported
Cloud
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