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Based on the provided context, I can confirm that the Jetson AGX Orin 64GB has two PCIe x8 slots available. However, to confirm the availability of these slots, I would recommend verifying the specific configuration of your Jetson AGX Orin 64GB module, as the context does not explicitly mention the 64GB variant.
Regarding your use case, I will break down the requirements and provide an analysis of each scenario.
Use Case 1:
- Device 1, 2, 3 at x2 lanes each (via lane splitter) → PCIe slot 1
- Device 4 at x4 lanes → PCIe slot 2
In this scenario, you are utilizing the two PCIe x8 slots, with the first slot split into three x2 lanes for Devices 1, 2, and 3, and the second slot used for Device 4 at x4 lanes. This configuration is feasible, as the Jetson AGX Orin supports PCIe Gen 3, which can provide sufficient bandwidth for your devices.
However, to ensure that the data from Devices 1, 2, and 3 is streamed in sync with no data drops, you will need to verify that the lane splitter is properly configured and that the devices are synchronized. Additionally, you should ensure that the PCIe slot 1 can handle the aggregated bandwidth of the three devices.
Use Case 2:
- Device 1, 2 at x4 lanes each (via lane splitter) → PCIe slot 1
- Device 3, 4 at x4 lanes each (via lane splitter) → PCIe slot 2
In this scenario, you are utilizing both PCIe x8 slots, with each slot split into two x4 lanes for Devices 1, 2 and Devices 3, 4, respectively. This configuration is also feasible, but you should verify that the lane splitters are properly configured and that the devices are synchronized.
Regarding your concern about retrieving data and sending it directly to the GPU for CUDA processing in a synced way, despite the two different slots, it is technically possible. However, it will depend on the specific implementation and the capabilities of your system.
The Jetson AGX Orin supports PCIe Gen 3, which provides a high-bandwidth interface for data transfer between the devices and the GPU. Additionally, the NVIDIA CUDA architecture allows for direct memory access (DMA) between the GPU and the PCIe devices, which can enable efficient data transfer and processing.
To achieve synced data transfer and processing, you may need to implement a custom solution that utilizes the CUDA API and the PCIe device drivers to manage the data transfer and synchronization between the devices and the GPU. This may require significant development and optimization efforts to ensure that the data is transferred and processed efficiently and in sync.
In summary, both use cases are feasible, but you should verify the specific configuration of your Jetson AGX Orin 64GB module and ensure that the lane splitters are properly configured. Additionally, you will need to implement a custom solution to achieve synced data transfer and processing between the devices and the GPU.
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