xilinx dpu user guide

This parameter specifies the PCIe BAR number where QDMA configuration register space is mapped. Petalinux . Software Tools and System Requirements. Refer to the Vitis AI User Guide (UG1414) and the Vitis AI Library User Guide (UG1354) for more information. So you need to fill the post-processing parameters according to the format defined in DpuModelParam.proto message. If you have a board that hasn't been marked as verified in the above table, you can use the new built-in tests to verify if DPU-PYNQ works on your device as intended. Consequently, only one stream (either the ML-processed stream or the original stream without ML) can be encoded for a single run. 5gIJ?.\NV0tTPlaNsBf2hdQS I-gE> VqaEgE>@Vh Documentation Navigator is optimally designed to support viewing and managing PDF documents. Color space conversion and scaling is done in a time division multiplexing (TDM) manner using Xilinx video processing IPs. Attach the VFs (here, 81:00.4 and 81:08.4) to VM via vfio-pci using QEMU with below command. 02/28/2019 Version 1.0 . The two layers are always full screen, matching the target display resolution. This command is used to read the specified register. The APIs we will use is included in the following header files: As shown in the figure above, developing applications based on the VART API, the red modules are the ones that need to be implemented by developers, the green modules encapsulate the DPU implementation. It also automatically extracts the mean and scale parameters and use them to do the algorithm pre-processes. Product Guide PG338 has a very detailed explanation of the Xilinx Deep Learning Processor Unit (DPU) and what ML operators it supports. The Preferences Tab provides several options for handling documents. Format for this commad is: This command reads the field info for the specified number of registers of the given port on console. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Closer objects appear in rainbow succession: green, yellow, orange, red, purple and finally white, closest to the camera. This command executes the list of CLI commands from the given file. From message DpuModelParam, first, we need to set the specific value to the ModelType. The captured frames are processed by ISP and broadcast over two ports. src-addr represents the source address (offset) in the card from where DMA should be done in memory mapped mode. Rebuild DPU Models The following table shows the resource usage for the Regulus ISP design: The following table shows the resource usage for the Xilinx ISP design: Next Topic: 3. If it doesn't fit the model, it resizes the image. Product updates, events, and resources in your inbox, Figure 8. 81:17.4 being the last one, represents port 7. Simply run: If the tests are successful please feel free to make a contribution to the above table by opening an pull request and updating the markdown entry for that board. 0>K,: This command is supported for VF port only. 3031 0 obj <>/Filter/FlateDecode/ID[<411186F215F75C4982E283F77A5A3166><2BF15AE49292F14A871C076BB41D61B0>]/Index[3011 152]/Info 3010 0 R/Length 118/Prev 1328014/Root 3012 0 R/Size 3163/Type/XRef/W[1 3 1]>>stream This field is ignored for streaming mode queues. The Settings Dialog is used to control preferences for handling documents, Internet settings, and providing information about the application configuration. The following figure shows a block diagram of the Smart Camera design. Obviously, the development of system-level pre-processing and algorithm-level post-processing, system-level post-processing functions are required. This section describes the details on controlling and configuring the QDMA IP. Looks like you have no items in your shopping cart. The same solution can be ported to use the Vitis AI libraries as well. Bind the VF device in VM to igb_uio driver and execute qdma_testapp in VM as outlined in section Running the DPDK software test application. www.xilinx.com 2 PG338 (v1.1) March 8, 2019 . In this case, we are using the function in xnnpp. The USB controller is part of the processing system (PS). Use this guide for developing and evaluating designs targeting the Zynq UltraScale+ XCZU9EG-2FFVB1156E MPSoC. The MIPI CSI2 Subsystem receives and decodes the incoming data stream to AXI4-Stream. Make sure you login as root (e.g., sudo su) and source the pynq profile scripts before installing the pynq_dpu package. Revision Summary . Create the a DpuTask with the kernel name which is generated from compiler "dnnc". So you don't need to care about the pre-processing. DPU IP Product Guide. The DP display pipeline uses the DRM/KMS Linux framework. However, one can also bind to vfio-pci driver, which provides more secure and IOMMU protected access to device. Use Git or checkout with SVN using the web URL. The struct CpuFlatTensorbuffer is the real image meta data container. One stream can be displayed on the DisplayPort without any processing, or can be encoded by the video codec unit (VCU) and transmitted over a network. It uses the standard Linux Universal Video Class (UVC) driver. The Frame Buffer Write IP writes the YUV422 stream to memory as packed YUYV format. Possible values for trigger_mode are: 2 Trigger when USER_COUNT threshold is reached, 3 Trigger when USER defined event is reached, 4 - Trigger when USER_TIMER threshold is reached. if the models under the support network list of Vitis AI library. This parameter enables or disables descriptor prefetch on C2H streaming queues. learn about Codespaces. Are you sure you want to create this branch? The modules in red need to be developed. Device specific parameters can be passed to a device by using the -w EAL option. The following examples show how to build and run the various computer vision accelerators on input and output live video. The other stream output from the broadcaster is converted to BGR and scaled down by the Multi-Scaler IP core (as required by the DPU IP) for ML processing. This example sets bypass mode on all the H2C queues belonging to the On host system, update /etc/default/grub file as below to enable IOMMU. Revision Summary . application and to interact with the QDMA PCIe device. Assuming that the VM image has been created with the settings outlined in Table Guest System Configuration, follow below steps to execute qdma_testapp on VM. Default is internal mode i.e. Add the Vendor Id and Device Id to vfio-pci and bind the VFs to vfio-pci as below, Follow below steps inside VM to bind the functions with vfio-pci, Running the DPDK software test application, /sys/bus/pci/devices/0000::., Supported Device arguments (module parameters), Commands supported by the qdma_testapp CLI, Executing with vfio-pci driver in VM using QEMU. Note that, if you use the post-processing function implemented on your own, you don't need to set the config parameters as xnnpp required. This example creates 1 VF for each PF. Overview. Machine learning (ML) is applied on received video data for both traffic detect and face detect functions using the Xilinx Deep Learning Processor Unit (DPU) IP as an accelerator, and the output streams are mixed to display on an HDMI monitor using the Xilinx HDMI Tx Subsystem IP. This parameter sets the trigger mode for completion. The development steps of neural network applications usually include: Generally, image frames from the sensor may need to be color converted or resized, which is a system design requirement, but not Artificial Intelligence algorithm requirements. Each layer of mixer takes data dumped by DeePhi after machine learning and shows it over HDMI after mixing. Once the VM is launched, execute steps as outlined in section, Bind the VF device in VM to vfio-pci driver and execute qdma_testapp in VM as outlined in section. Take resnet50 as an example which is using the model resnet50, the source code you could refer toresnet50 sample. This design is available on the ZCU104 board only. For post-processing, you can adapt the model and the application needs b. The Video Processing Subsystem converts the incoming color format (RGB, YUV444, or YUV422) to YUV422 and optionally scales the image to the target resolution. This command resets the DPDK port. Figure 10: DPU Configuration Updated figure. Vitis AI Library encapsulates all models according to the requirements of each model. A program . Take the configuration file defined in the example demo_yolov3.cpp as an example. Above section binds PFs and VFs with igb_uio driver. Once the VM is launched, execute steps as outlined in section Building QDMA DPDK Software to build DPDK on VM. The ZCU104 Single Sensor platform supports the following video interfaces. These hardware designs are similar to earlier vision platforms used with SDSoC tools. face co-ordinates) from input frames using DPU IP and pass the detected ROI information to the Xilinx VCU encoder. With different levels of APIs, the requirements can be divided into three categories. For a selection of smaller boards, like the Ultra96 and ZUBoard-1CG custom arch.json files are provided that will allow you to compile .xmodel files for those boards. Face detection is shown by boxes encircling detected faces. It is clear from here that the implementation of DpupuTask highly depends on the implementation of DpuRunner. Navigate to examples/qdma_testapp directory. In either case, all 8 streams should be H.264/H.265 encoded: The ZCU104 Smart Camera platform supports the following video interfaces. Add CE for dpu_2x_clk; Reset; Development Flow; Customizing and Generating the Core in the Zynq UltraScale+ MPSoC; Add DPU IP into Repository or Upgrade DPU from a Previous Version; Add DPU IP into Block Design; Configure DPU Parameters; Connecting a DPU to the Processing System in the Zynq UltraScale+ MPSoC; Assign Register Address for DPU; Generate Bitstream The DP display pipeline is configured for dual-lane mode, and is part of the PS. 1. It is a group of parameterizable IP cores pre-implemented on the hardware with no place and route required. I used dpu integration tutorial to generate custom hardware for 2 different cases to com This field is ignored for streaming mode queues. This example sets completion entry length to 32 bytes on all the completion queues The header files related to VART APIs are distributed in the following header files. The Demosaic IP converts the raw image format to RGB. The GStreamer plugin demonstrates the DPU capabilities with Xilinx VCU encoder's ROI (Region of Interest) feature. ring-depth represents the number of entries in C2H and H2C descriptor rings of each queue of the port, pkt-buff-size represents the size of the data that a single C2H or H2C descriptor can support. In short, the following files will be generated in boards/ folder: These are the overlay files that can be used by the pynq_dpu package. The following table shows the revision history for this document. Are you sure you want to create this branch? Vitis AI Library APIs structure, Deep Learning Training vs Inference: Differences, Single- vs. Double- vs Multi-Precision Computing, Monetize AV content and optimize media workflows, Realizing Dense, Low Cost-per-Channel TV Modulation, Real-Time UHD Video Processing & Audio DSP, Save Bandwidth, Storage and Costs with Codecs, Clinical Defibrillators & Automated External Defibrillators, Diagnostic & Clinical Endoscopy Processing, Programming an FPGA: Introduction to How It Works, Developer's Guide to Blockchain Development. For the ZCU104 Smart Camera platform, there are two design examples: one uses Xilinx ISP, and the other uses Regulus ISP. Xilinx DPU IP Manuals & User Guides User Manuals, Guides and Specifications for your Xilinx DPU IP Computer Hardware. The scope of the developer's implementation includes color conversion, decoding, and algorithm level for video and image data, such as mean and scale, then create a DPU runner with the prepared data via VART. Format for this commad is: num-queues represents the total number of queues to use to receive the data, output-filename represents the path to output file to dump the received data. The HDMI display pipeline uses the DRM/KMS Linux framework. This example configures BAR 2 as QDMA configuration BAR for device 81:00.0 So for this case, what you need to do is to read an image, and then send it to the run() method in the instance of class Facedetect. The stereo block-matching algorithm calculates depth based on binocular parallax, similar to the way human eyes perceive depth. 5 - Trigger when either of USER_TIMER or COUNT is reached. If i want to use the DPU on the bare-metal application without OS, what should i do? If nothing happens, download Xcode and try again. The MIPI capture pipeline is implemented in the PL and consists of the Sony IMX274 image sensor, the MIPI CSI2 Subsystem, the Demosaic IP, the Gamma IP, the Video Processing Subsystem (CSC configuration), a Video Processing Subsystem (Scaler-only configuration), and the Frame Buffer Write IP. Reboot host system after making the above modifications. This example enables descriptor prefetch on all the streaming C2H queues of For using Vitis AI Library APIs to build applications, developers don't need to implement the post-processing by themselves. The depth map is coded in false colors. 2nd queue receives (524288/2048) bytes of data from BRAM offset (1*524288)/2048, and so on. The following table shows the performance matrix for this platform. Four IP camera traffic streams and four streams from a laptop, 8 streams from the laptop alone (H.264/H.265 encoded File I/O). The optical flow algorithm returns two signed numbers at each pixel position, representing up or down motion in the vertical direction, and left or right motion in the horizontal direction. Customizing and Generating the Core in the Zynq UltraScale+ MPSoC. This command closes the port and re-initializes it with the values provided in this command. Video sources (or capture pipelines) are shown on the left. You signed in with another tab or window. Vitis AI Library optimized codes for entire algorithmic flow open and flexible architecture for easy extension directly support models inModel Zoo. You don't have access just yet, but in the meantime, you can Copy the pre-processed data to the inputTendor pointer, run the runner, and then get the outputTensor. Set to YOLOv3, the following parameters should be set to yolov3param accordingly. This command is used to write a 32-bit value to the specified register. the device 81:00.0. Currently, the design is configured to use only one channel of the VCU. This command frees up all the allocated resources and removes the queues associated with the port. The Vitis AI User Guide (UG1414) describes how to use the DPUCZDX8G with the Vitis AI tools. a03f, a13f) of the VFs being attached to VM using lspci command. The DpuTask APIs are built on top of VART, as apposed to VART, the DpuTask APIs encapsulate not only the DPU runner but also the algorithm-level pre-processing, such as mean and scale. Vitis AI RunTime(VART) is built on top of XRT, VART uses XRT to build the 5 unified APIs. In total, 8 ports are serially arranged as shown above, The next step is to prepare the input/output tensor buffers and fill the input buffer with the image data and tensor shape information. vfio-pci doesnt provide sysfs interface to enable VFs. Format for this commad is: num-queues represents the total number of queues to use for transmitting the data, input-filename represents the path to a valid binary data file, contents of which needs to be DMAed. Deep learning algorithms are becoming more popular for IoT applications on the edge because of human-level accuracy in object recognition and classification. My problem is that I also have to include the DPU drivers into the PetaLinux . Format for this commad is: This example removes the port 4. The deep-learning processor unit (DPU) is a programmable engine optimized for deep neural networks. The DPU requires instructions to implement a neural network and accessible memory locations for input images as well as temporary and output data. Add the DPUCZDX8G into Repository or Upgrade the DPUCZDX8G from a Previous Version. Zynq DPU v3.1 IP Product Guide - 3.1 English pg338-dpu.pdf Document ID PG338 Release Date 2019-12-02 Version 3.1 English Back to home page With a dilation of 6, the number of output parameters will be 6143 which is too many for the DPU to capture." In tutorial it says DPU only supports 12 bits to describe the number of parameters, but I could not find about this in DPU Product Guide . In the run() of DetectImp, the post-processing function will be called after the configurable_dpu_task_->run() finished. I've created an .xsa file to configure the PetaLinux project, which includes all necessary connections between DPU and Processor System. The DpuRunnerExt derived from DpuRunner with the extension of some APIs that are used to get the fixed information of the model after compiled into an elf format. When we push back the CpuFlatTensorBuffer pointer down to the TensorBuffer pointer's container, the preparation of the data is complete. 03/08/2019 Version 1.1 . Xilinx DPU IP Product manual (43 pages) Pages: 43 | Size: Xilinx DPU IP Related Products Xilinx FMC XM107 New DPU support - Besides DPUv2 for Zynq and ZU+, a new AI Library will support new DPUv3 IPs for Alveo/Cloud using same codes (Early access). Valid values are. PetaLinux DPU driver. We use these unified API to process the DPU running part. size represents the amount of data in bytes that needs to be transmitted to the card from the given input file. Copy the DPDK source code in VM by executing below command from VM. The HDMI capture pipeline uses the V4L Linux framework. This parameter sets the H2C bypass mode. The HDMI TX Subsystem encodes the incoming video into an HDMI data stream and sends it to the HDMI display. You need to be careful, the post-processing function defined in xnnpp required the specific config parameters. This parameter sets the C2H stream mode. To load an image, the run() method checks the size of the image in the created Faceddetect object. where 81:00.0 represents port 0, 81:00.1 represents port 1 and so on. To enable simultaneous streams, the design needs to be modified to support multiple streams in the VCU IP. Configure DPUCZDX8G Parameters. DPU overlays for most boards have been built using the B4096 architecture with 1 or 2 cores, compatible with the KV260/ZCU102/ZCU104 models in the Vitis AI Model Zoo. Video sinks (or output/display pipelines) are shown on the right. This example sets simple bypass mode on all the C2H queues belonging to the To open the Settings Dialog, click the icon located on the Main Toolbar. This article aims to explain the difference between the 3 levels of Vitis AI Library APIs. Furthermore, DpuTask allows you to independently implement and invoke the post-processing function. This is widely used in image filters to achieve popular image effects like blur, sharpen, and edge detection. The format of the config file needs to follow the message YoloV3Param in the protobuf below. The MIPI capture is implemented in the PL. The Vitis AI Library contains three different levels of APIs, how to choose the one that is right for your development API, which is important for reducing development and improving performance. Vitis-AI. This command dumps the queue context of the specified queue number of the given port. Revision History . Before joining Xilinx in July 2018, he served as Product leads of Deephi business department. A tag already exists with the provided branch name. User will need to restart the application to use the port again. All that's left is to execute the dpu runner, get the results back, send the results to the post-processing function, display the results, and finish the whole process. After extract the above parameters, how to determine the physical address of these parameters to write these parameters into DRAM on board? Format for this commad is: This example command resets the port 4 and re-initializes it with first 16 queues in streaming mode and Both system/non-AI pre-processing and post-processing are system-level, depending on scenarios, such as performing color conversion and resizing for metadata from the camera or video transfer devices, processing detection bounding boxes to capture photos or generate alerts. This implies that the (num-queues - num-st-queues) number of queues has to be configured in memory mapped mode. If nothing happens, download GitHub Desktop and try again. ZCU102 Board User Guide (UG1182) ug1182-zcu102-eval-bd.pdf Setting the mean and scale parameters into DpuTask. Format for this commad is: queue-id represents the queue number relative to the port, whose C2H and H2C ring descriptors needs to be dumped. First of all, you need to create runner and get the tensorshape needed for DPU runner, such as height, width, channel, and size. Xilinx RunTime(XRT) is unified base APIs. Take test_jpg_facedetect.cpp as an example, the default value of need_preprocess is true. %%EOF The post-processing library can be used as a reference. Thirdly, The run() function of DetectImp includes the pre-processing/ run the dpuTask/post-processing. Note: Port 0 can again be re-initialized with port_init command after port_close command. Installation and Operating Instructions, dpu_top_1 (machine learning IP built using the Vitis software platform), axis_broadcaster_0 (zcu104_smart_camera_axis_broadcaster_0_0), mipi_csi2_rx_subsystem_0 (zcu104_smart_camera_mipi_csi2_rx_subsystem_0_0), v_frmbuf_wr_0 (zcu104_smart_camera_v_frmbuf_wr_0_0), v_frmbuf_wr_1 (zcu104_smart_camera_v_frmbuf_wr_1_0), v_proc_ss_0 (zcu104_smart_camera_v_proc_ss_0_0), v_proc_ss_1 (zcu104_smart_camera_v_proc_ss_1_0), sensor_iic_0 (zcu104_smart_camera_sensor_iic_0_0), v_multi_scaler_0 (zcu104_smart_camera_v_multi_scaler_0_0), v_demosaic_0 (zcu104_smart_camera_v_demosaic_0_0), v_gamma_lut_0 (zcu104_smart_camera_v_gamma_lut_0_0), USB2/3 camera up to 1080p60 or stereo 1080p30. If you want to rebuild the hardware project, you can refer to the Enable VF(s) on host system by writing the number of VF(s) to enable in max_vfs file under /sys/bus/pci/devices/0000::.. Start qdma_testapp application on host system, Start the VM using below command by attaching the VF (81:00.4 in this example). The DPUCZDX8G requires a device driver which is included in the Xilinx Vitis AI development kit. Resize is the system level pre-processing, mean and scale are the algorithm-level pre-processing. Take facedect sample as an example, the source code refers tofacedetect.cpp. In short, the following files will be generated in boards/<Board> folder: dpu.bit; dpu.hwh; dpu.xclbin; These are the overlay files that can be used by the pynq_dpu package. Data will be segmented across queues such that the total data transferred from the card is size amount. DPU V3E is a high-performance CNN inference IP optimized for throughput and data center workloads. If you want to recompile the DPU models or train your own network, you can refer to the and transmits the segmented data on each queue starting at destination BRAM offset 0 for 1st queue, Revision History .

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