Getting Started with Graphcloud
Version: latest
1. Graphcloud overview
1.1. Prerequisites
1.1.1. Linux and Python commands
1.1.2. Managing the IPU hardware resources
2. Accessing Graphcloud
2.1. Your account
2.1.1. Logging in
2.1.2. Adding more users
2.1.3. Extending access to Graphcloud
2.1.4. Closing your account
2.2. Configuration overview
2.2.1. Local storage
2.3. Software and datasets
2.4. Making efficient use of local storage
2.4.1. Shared workspace
2.4.2. Installing the Graphcore examples
2.4.3. Temporary storage
3. Software setup
3.1. Setting up the SDK environment
3.2. Setting up PyTorch for the IPU
3.3. Setting up TensorFlow for the IPU
3.3.1. IPU TensorFlow Addons
3.3.2. Next steps
3.4. Verifying the hardware configuration
4. Running a program on the IPU
4.1. Hardware and software monitoring
4.1.1. Command line tools
4.1.2. Trace output
4.1.3. Execution profiling
5. Troubleshooting
6. Next steps
7. Trademarks & copyright
Getting Started with Graphcloud
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Getting Started with Graphcloud
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Getting Started with Graphcloud
ΒΆ
1. Graphcloud overview
1.1. Prerequisites
1.1.1. Linux and Python commands
1.1.2. Managing the IPU hardware resources
2. Accessing Graphcloud
2.1. Your account
2.1.1. Logging in
2.1.2. Adding more users
2.1.3. Extending access to Graphcloud
2.1.4. Closing your account
2.2. Configuration overview
2.2.1. Local storage
2.3. Software and datasets
2.4. Making efficient use of local storage
2.4.1. Shared workspace
2.4.2. Installing the Graphcore examples
2.4.3. Temporary storage
3. Software setup
3.1. Setting up the SDK environment
3.2. Setting up PyTorch for the IPU
3.3. Setting up TensorFlow for the IPU
3.3.1. IPU TensorFlow Addons
3.3.2. Next steps
3.4. Verifying the hardware configuration
4. Running a program on the IPU
4.1. Hardware and software monitoring
4.1.1. Command line tools
4.1.2. Trace output
4.1.3. Execution profiling
5. Troubleshooting
6. Next steps
7. Trademarks & copyright
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