diff --git a/default.conf b/default.conf index aa016cd6..cc7322b4 100644 --- a/default.conf +++ b/default.conf @@ -541,17 +541,5 @@ server { location ~ ^/docs/account-settings/create-an-account-for-an-individual-or-legal-entity?$ { return 301 https://$host/docs/account-settings/create-account/create-an-account-for-an-individual-or-legal-entity ; } location ~ ^/docs/account-settings/create-an-additional-account-and-switch-between-main?$ { return 301 https://$host/docs/account-settings/create-account/create-an-additional-account-and-switch-between-main ; } - ####PIN-846 - location ~ ^/docs/cloud/inference-at-the-edge?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge ; } - location ~ ^/docs/cloud/inference-at-the-edge/prepare-custom-model-for-deployment?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/prepare-custom-model-for-deployment ; } - location ~ ^/docs/cloud/inference-at-the-edge/manage-deployments?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/manage-deployments ; } - location ~ ^/docs/cloud/inference-at-the-edge/create-and-manage-api-keys?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/create-and-manage-api-keys ; } - location ~ ^/docs/cloud/inference-at-the-edge/add-a-registry?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/add-a-registry ; } - location ~ ^/docs/cloud/inference-at-the-edge/deploy-models/deploy-ai-model?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/deploy-models/deploy-ai-model ; } - location ~ ^/docs/cloud/inference-at-the-edge/deploy-models/deploy-huggingface-models?$ { return 301 https://$host/docs/edge-ai/inference-at-the-edge/deploy-models/deploy-huggingface-models ; } - location ~ ^/docs/cloud/ai-Infrustructure/about-our-ai-infrastructure?$ { return 301 https://$host/docs/edge-ai/ai-infrastructure/about-our-ai-infrastructure ; } - location ~ ^/docs/cloud/ai-Infrustructure/create-an-ai-cluster?$ { return 301 https://$host/docs/edge-ai/ai-infrastructure/create-an-ai-cluster ; } - location ~ ^/docs/cloud/ai-Infrustructure/about-virtual-vpod?$ { return 301 https://$host/docs/edge-ai/ai-infrastructure/about-our-ai-infrastructure ; } - location ~ ^/(.*)/$ { return 301 https://$host/$1; } } diff --git a/documentation/edge-ai/ai-infrastructure/about-our-ai-infrastructure.md b/documentation/edge-ai/ai-infrastructure/about-our-ai-infrastructure.md deleted file mode 100644 index 84167866..00000000 --- a/documentation/edge-ai/ai-infrastructure/about-our-ai-infrastructure.md +++ /dev/null @@ -1,133 +0,0 @@ ---- -title: about-our-ai-infrastructure -displayName: About GPU Cloud -order: 10 -published: true -toc: - --1--AI GPU infrastructure: "ai-gpu-infrastructure" - --1--Tools our AI Infrastructure supports: "tools-supported-by-gcore-gpu-cloud" -pageTitle: About Gcore GPU Cloud | Gcore -pageDescription: Explore Gcore GPU Cloud for AI. NVIDIA servers, top performance, diverse tool support. Easy deployment, per-minute billing. ---- -# GPU Cloud infrastructure - -Gcore GPU Cloud provides high-performance compute clusters designed for machine learning tasks. - -## AI GPU infrastructure - -Train your ML models with the latest NVIDIA GPUs. We offer a wide range of Bare Metal servers and Virtual Machines powered by NVIDIA A100, H100, and L40S GPUs. - -Pick the configuration and reservation plan that best fits your computing requirements. - -
Specification | -Characteristics | -Use case | -Performance | -
---|---|---|---|
H100 with Infiniband | -
- 8x Nvidia H100 80GB - 2 Intel Xeon 8480+ - 2TB RAM - 2x 960GB - 8x3.84 TB NVMe - 3.2 Tbit/s Infiniband - 2x100Gbit/s Ethernet - |
- - Optimized for distributed training of Large Language Models. - | -Ultimate performance for compute-intensive tasks that require a significant exchange of data by the network. | -
A100 with Infiniband | -
- 8x Nvidia A100 80GB - 2 Intel Xeon 8468 - 2 TB RAM - 2x 960GB SSD - 8x3.84 TB NVMe - 800Gbit/s Infiniband - |
- - Distributed training for ML models and a broad range of HPC workloads. - | -Well-balanced in performance and price. | -
A100 without Infiniband | -
- 8x Nvidia A100 80GB - 2 Intel Xeon 8468 - 2 TB RAM - 2x 960GB SSD - 8x3.84 TB NVMe - 2x100Gbit/s Ethernet - |
-
- Training and fine-tuning of models on single nodes. - Inference for large models. - Multi-user HPC cluster. - |
- The best solution for inference models that require more than 48GB vRAM. | -
L40 | -
- 8x Nvidia L40S - 2x Intel Xeon 8468 - 2TB RAM - 4x7.68TB NVMe SSD - 2x25Gbit/s Ethernet - |
-
- Model inference. - Fine-tuning for small and medium-size models. - |
- The best solution for inference models that require less than 48GB vRAM. | -
Tool class | -List of tools | -Explanation | -
---|---|---|
Framework | -TensorFlow, Keras, PyTorch, Paddle Paddle, ONNX, Hugging Face | -Your model is supposed to use one of these frameworks for correct work. | -
Data platforms | -PostgreSQL, Hadoop, Spark, Vertika | -You can set up a connection between our cluster and your data platforms of these types to make them work together. | -
Programming languages | -JavaScript, R, Swift, Python | -Your model is supposed to be written in one of these languages for correct work. | -
Resources for receiving and processing data | -Storm, Spark, Kafka, PySpark, MS SQL, Oracle, MongoDB | -You can set up a connection between our cluster and your resources of these types to make them work together. | -
Exploration and visualization tools | -Seaborn, Matplotlib, TensorBoard | -You can connect our cluster to these tools to visualize your model. | -