Trainy
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About
Trainy provides enterprise-grade GPU infrastructure for AI training, allowing users to run large-scale GPU workloads on-demand or on dedicated GPUs. It simplifies deployment with simple YAML files, handling networking, scaling, and issue resolution. Trainy supports various ML frameworks like PyTorch, HuggingFace, Jax, and Ray, enabling multi-node setups and cross-cloud compatibility. It features high reliability with fault detection, automatic recovery, and real-time visibility into GPU usage and costs. The platform offers flexible on-demand pricing, charging only for active training time, and also provides reserved plans for dedicated GPU allocation.
Platform
Features
• run large scale gpu workloads on-demand
• preemptive queueing & resource management
• real-time gpu usage and cost visibility
• high reliability: fault detection, automatic recovery, zero downtime
• support for any ml frameworks (pytorch, huggingface, jax, ray)
• cross-cloud compatibility & multi-node setup
• scale across 1000s of gpus with high bandwidth networking
• quick setup: up & running in minutes, zero code changes
FAQs
How do I submit jobs with Trainy?
Submitting jobs in Trainy’s platform is done via a simple YAML file. You just need to enter your existing torchrun or equivalent launch command and our platform handles the rest.
Is Trainy a Cloud Provider?
No. We help customers pick a cloud provider offering, assist with hardware validation, and can deploy on-prem or in the cloud. We help startups go from cloud credits to a functional multinode training setup.
Should my AI team access GPUs via On-Demand or Reserved?
Most Trainy customers use a hybrid. Reserved instances generally make sense for inference servers and dev boxes. On-demand allows bursting to larger scale at a lower cost, reducing GPU spend.
Kubernetes seems too complicated. Why do I need software to manage my GPUs?
Kubernetes gives AI teams higher ROI. With automated scheduling and cleanup of queued workloads, AI engineers never worry about GPU availability. Decision makers get improved visibility and control.
What are the benefits of Trainy over a tool like Slurm?
Trainy offers all of Slurm's benefits with more, including better workload isolation via containerization, integrated observability, and improved robustness with comprehensive health monitoring.
How does Trainy cut GPU costs?
Trainy cuts GPU costs by minimizing idle time with fault-tolerant scheduling to keep GPUs busy 24/7. Advanced performance metrics also help optimize workload efficiency.
How do I connect data sources to my GPU cluster with Trainy’s platform?
Most Trainy customers stream data into their GPU cluster from object stores like Cloudflare R2. Distributed file system integrations are being explored but are not available today.
Can I use Trainy to manage multi-cloud environments?
We can give your team access to multiple Kubernetes clusters corresponding to different clouds, but jobs are submitted to one cluster at a time.
What is the best time to start working with Trainy?
The earlier, the better. On-demand clusters are cost-effective for exploring Gen AI applications. We also help navigate cloud provider offerings to ensure maximum performance.
Pricing Plans
On-Demand
USD3.60 / per GPU per hour• High-Performance Cluster (8xH100 GPUs, 80GB SXM5, 3.2Tb/s Infiniband)
• Zero code changes required
• Multi-node training support
• High-bandwidth networking
• Cross-cloud compatibility
• Priority queuing system
• Dashboard access, Queue management, Team access controls
• Automated job failure recovery
• 24x7 Always-On Support
• 99.5% Uptime SLA
Reserved
USD50000.00 / per year• High-Performance Cluster (8xH100 GPUs, 80GB SXM5, 3.2Tb/s Infiniband)
• Zero code changes & Multi-node training
• High-bandwidth networking & Cross-cloud compatibility
• Priority queuing system
• Dashboard access, Queue management, Team access controls
• Automated job failure recovery
• 24x7 Always-On Support
• 99.5% Uptime SLA
• Dedicated GPU allocation (Blackwell, All NVIDIA Data Center GPUs)
• Advanced monitoring, Cluster utilization insights, GPU health monitoring, Enterprise SLA
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
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