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Update README
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@ -19,8 +19,6 @@ We present pre-packaged containers supporting CUDA 11.x & CUDA 12.x with pre-bui
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This means multiple containers can be launched on the same GPU, ensuring one user cannot allocate the entire host GPU memory!
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This means multiple containers can be launched on the same GPU, ensuring one user cannot allocate the entire host GPU memory!
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(No more greedy processes grabbing the entire GPU memory! Finally we have a driver level hard limiting memory option).
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(No more greedy processes grabbing the entire GPU memory! Finally we have a driver level hard limiting memory option).
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![Fractional GPU diagram](docs/fractional_gpu_diagram.png)
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## 🚀 Offerings
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## 🚀 Offerings
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ClearML offers several options to optimize GPU resource utilization by partitioning GPUs:
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ClearML offers several options to optimize GPU resource utilization by partitioning GPUs:
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@ -38,6 +36,7 @@ With these options, ClearML enables running AI workloads with optimized hardware
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This repository covers container-based fractional GPUs. For more information on ClearML's fractional GPU offerings, see
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This repository covers container-based fractional GPUs. For more information on ClearML's fractional GPU offerings, see
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the [ClearML documentation](https://clear.ml/docs/latest/docs/clearml_agent/clearml_agent_fractional_gpus).
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the [ClearML documentation](https://clear.ml/docs/latest/docs/clearml_agent/clearml_agent_fractional_gpus).
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![Fractional GPU diagram](docs/fractional_gpu_diagram.png)
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## ⚡ Installation
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## ⚡ Installation
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