watonomous.github.io

[ Software Division : Fall 2019 Progress and Notes ]

Created by [ Rowan Dempster] on Dec 28, 2019

Dev Cycle 1

https://www.intel.com/content/www/us/en/programmable/documentation/tgy1490191698959.html
guide to get the fpga working

quartus_pgm cannot find the libxerc 32https://forums.intel.com/s/question/0D50P00004IpHt2/error-opening-quartus-or-compiling-opencl-files-asthis-is-happening-with-quartus-191-any-env-variable-i-am-missingquartus-error-while-loading-shared-libraries-libxercesc32so-cannot-open-shared-object-file-no-such-file-or-directory?language=en_US

https://forums.intel.com/s/question/0D50P00004IpHt2/error-opening-quartus-or-compiling-opencl-files-asthis-is-happening-with-quartus-191-any-env-variable-i-am-missingquartus-error-while-loading-shared-libraries-libxercesc32so-cannot-open-shared-object-file-no-such-file-or-directory?language=en_US

this was fixed through the above

Dev Cycle 2

following https://docs.openvinotoolkit.org/2019_R1.1/_docs_install_guides_GX_Configure_2019R1.html
got aocl working and inference seems to work

root@AUTODRIVE-BOLT:/home/test/inference_engine_samples_build/intel64/Release# ./classification_sample -i car.png -m /home/test/openvino_models/ir/FP32/classification/squeezenet/1.1/caffe/squeezenet1.1.xml -d HETERO:FPGA,CPU -ni 1000
[ INFO ] InferenceEngine: 
    API version ............ 1.6
    Build .................. custom_releases/2019/R1.1_28dfbfdd28954c4dfd2f94403dd8dfc1f411038b
[ INFO ] Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ]     car.png
[ INFO ] Loading plugin

    API version ............ 1.6
    Build .................. heteroPlugin
    Description ....... heteroPlugin
[ INFO ] Loading network files:
    /home/test/openvino_models/ir/FP32/classification/squeezenet/1.1/caffe/squeezenet1.1.xml
    /home/test/openvino_models/ir/FP32/classification/squeezenet/1.1/caffe/squeezenet1.1.bin
[ INFO ] Preparing input blobs
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[ INFO ] Batch size is 1
[ INFO ] Preparing output blobs
[ INFO ] Loading model to the plugin
Error: Could not load board library /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so (error_msg: /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so: cannot open shared object file: No such file or directory)
Failed to dynamically load board MMD /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so
Error: Could not load board library /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so (error_msg: /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so: cannot open shared object file: No such file or directory)
Failed to dynamically load board MMD /opt/altera/aocl-pro-rte/aclrte-linux64/board/hddlf_1150_sg1/linux64/lib/libaltera_a10_1150_sg1_mmd.so
[ INFO ] Starting inference (1000 iterations)
[ INFO ] Processing output blobs

Top 10 results:

Image car.png

classid probability label
------- ----------- -----
817     0.8931729   sports car, sport car
511     0.0444685   convertible
479     0.0444685   car wheel
436     0.0060182   beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon
751     0.0060182   racer, race car, racing car
656     0.0022140   minivan
864     0.0008145   tow truck, tow car, wrecker
717     0.0008145   pickup, pickup truck
586     0.0008145   half track
581     0.0002996   grille, radiator grille


total inference time: 1503.0926671
Average running time of one iteration: 1.5030927 ms

Throughput: 665.2949761 FPS



[ INFO ] Execution successful

Dev Cycle 3 & 4

terminate called after throwing an instance of 'InferenceEngine::details::InferenceEngineException'
  what():  Error: One of the following environment variables must be defined: DLA_AOCX or CL_CONTEXT_COMPILER_MODE_INTELFPGA=3

[ INFO] [1572913657.585308102]: Param output_frame_name: world
terminate called after throwing an instance of 'InferenceEngine::details::InferenceEngineException'
  what():  Graph is not supported on FPGA plugin due to existance of layer (Name: FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6, Type: Clamp)
in topology. Most likely you need to use heterogeneous plugin instead of FPGA plugin directly.

/opt/intel/computer_vision_sdk/deployment_tools/inference_engine/include/details/ie_exception_conversion.hpp:71
[ ERROR ] Graph is not supported on FPGA plugin due to existance of layer (Name: LeakyReLU_3838, Type: ReLU)
in topology. Most likely you need to use heterogeneous plugin instead of FPGA plugin directly.

Steps to run the FPGA:
https://docs.openvinotoolkit.org/2019_R1.1/_docs_install_guides_GX_Configure_2019R1.html

first set the jtagconfig clock to 6M

jtagconfig --getparam 1 JtagClock

flash the board with default SOF and POF

quartus_pgm -c 1 -m JTAG -o "p;max5_150.pof@2"
quartus_pgm -c 1 -m JTAG -o "p;top.sof"

Restart
install aocl by typing ` aocl install `
Restart again
aocl diagnose should say success
Program a bistream

any bitstream works
ex:

aocl program acl0 /opt/intel/openvino/bitstreams/a10_devkit_bitstreams/2019R1_A10DK_FP11_SqueezeNet.aocx

you should be able to run sample applications

more details

https://docs.openvinotoolkit.org/2019_R1.1/_docs_install_guides_GX_Configure_2019R1.html

Running

roscore
rosbag play (some bag)
roslaunch perception perception-vehicle-exp-fpga.launch

gives result

aunch perception-vehicle-exp-fpga.launch 
... logging to /home/autodrive/.ros/log/51f012e8-04e6-11ea-8808-ac1f6b056632/roslaunch-AUTODRIVE-BOLT-72293.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
WARNING: disk usage in log directory [/home/autodrive/.ros/log] is over 1GB.
It's recommended that you use the 'rosclean' command.

started roslaunch server http://AUTODRIVE-BOLT:35715/

SUMMARY
========

PARAMETERS
 * /perception/clip_cloud: True
 * /perception/clip_max_height: 5.0
 * /perception/clip_min_height: 0.2
 * /perception/cluster_merge_threshold: 1.5
 * /perception/cluster_size_max: 500
 * /perception/cluster_size_min: 5
 * /perception/clustering_distances: [15, 30, 45, 60]
 * /perception/clustering_thresholds: [0.5, 1.1, 1.6, 2...
 * /perception/downsample_cloud: False
 * /perception/downsample_leaf_size: 0.2
 * /perception/frame_pub_topic: /camera/image_color
 * /perception/img_test_dir: /home/watonomous/...
 * /perception/keep_lane_left_distance: 5.0
 * /perception/keep_lane_right_distance: 5.0
 * /perception/keep_lanes: False
 * /perception/lidar_name_list: ['/velodyne_points']
 * /perception/lidar_output_frame: world
 * /perception/lidar_scales: [2.0]
 * /perception/lidar_tf_list: [0, 0, 2.06, 0, 0...
 * /perception/nn_hardware: HETERO:FPGA,CPU
 * /perception/nn_obstacle_model_path: /home/autodrive/i...
 * /perception/nn_segmentation_model_path: /home/autodrive/i...
 * /perception/nn_traffic_sign_model_path: /home/autodrive/i...
 * /perception/obj_nn_hardware: CPU
 * /perception/pose_estimation: False
 * /perception/remove_ground: True
 * /perception/remove_points_upto: 0.0
 * /perception/rm_ground_max_angle: 0.1
 * /perception/rm_ground_max_height: 0.2
 * /perception/use_diffnormals: False
 * /rosdistro: kinetic
 * /rosversion: 1.12.14

NODES
  /
    object_detection_node (perception/object_detection_node)
    obstacle_detection_node (perception/obstacle_detection_node)
    rviz (rviz/rviz)
    traffic_light_detection_node (perception/traffic_light_detection_node)
    traffic_sign_detection_node (perception/traffic_sign_detection_node)

ROS_MASTER_URI=http://localhost:11311

process[traffic_light_detection_node-1]: started with pid [72310]
/home/autodrive/integration/devel/lib/perception/traffic_light_detection_node: /opt/altera/quartus/linux64/liblzma.so.5: no version information available (required by /usr/lib/x86_64-linux-gnu/libtiff.so.5)
process[traffic_sign_detection_node-2]: started with pid [72311]
/home/autodrive/integration/devel/lib/perception/traffic_sign_detection_node: /opt/altera/quartus/linux64/liblzma.so.5: no version information available (required by /usr/lib/x86_64-linux-gnu/libtiff.so.5)
process[obstacle_detection_node-3]: started with pid [72312]
/home/autodrive/integration/devel/lib/perception/obstacle_detection_node: /opt/altera/quartus/linux64/liblzma.so.5: no version information available (required by /usr/lib/x86_64-linux-gnu/libtiff.so.5)
process[object_detection_node-4]: started with pid [72314]
process[rviz-5]: started with pid [72325]
/opt/ros/kinetic/lib/rviz/rviz: /opt/altera/quartus/linux64/libssl.so.1.0.0: no version information available (required by /usr/lib/x86_64-linux-gnu/libcurl.so.4)
/opt/ros/kinetic/lib/rviz/rviz: /opt/altera/quartus/linux64/libssl.so.1.0.0: no version information available (required by /usr/lib/x86_64-linux-gnu/libcurl.so.4)
/opt/ros/kinetic/lib/rviz/rviz: /opt/altera/quartus/linux64/libssl.so.1.0.0: no version information available (required by /usr/lib/x86_64-linux-gnu/libcurl.so.4)
/opt/ros/kinetic/lib/rviz/rviz: /opt/altera/quartus/linux64/libcrypto.so.1.0.0: no version information available (required by /usr/lib/x86_64-linux-gnu/libcurl.so.4)
/opt/ros/kinetic/lib/rviz/rviz: /opt/altera/quartus/linux64/liblzma.so.5: no version information available (required by /usr/lib/x86_64-linux-gnu/libtiff.so.5)
This application failed to start because it could not find or load the Qt platform plugin "xcb"
in "".

Reinstalling the application may fix this problem.
[ INFO] [1573519988.995210978]: Got param: perception/lidar_tf_list

[ INFO] [1573519988.997745412]: Got param: perception/lidar_name_list

[ INFO] [1573519989.001843973]: Got param: perception/lidar_scales

[ INFO] [1573519989.005899740]: Param output_frame_name: world
[rviz-5] process has died [pid 72325, exit code -6, cmd /opt/ros/kinetic/lib/rviz/rviz -d /home/autodrive/integration/src/perception-year-2/perception_config.rviz __name:=rviz __log:=/home/autodrive/.ros/log/51f012e8-04e6-11ea-8808-ac1f6b056632/rviz-5.log].
log file: /home/autodrive/.ros/log/51f012e8-04e6-11ea-8808-ac1f6b056632/rviz-5*.log
[ INFO] [1573519993.142630999]: Euclidean Clustering: Difference of Normals will not be used.
[ INFO] [1573519993.143533442]: downsample_cloud: 0
[ INFO] [1573519993.144492598]: remove_ground: 1
[ INFO] [1573519993.145717309]: leaf_size: 0.200000
[ INFO] [1573519993.146633842]: cluster_size_min: 5
[ INFO] [1573519993.147559619]: cluster_size_max: 500
[ INFO] [1573519993.148500777]: pose_estimation: 0
[ INFO] [1573519993.149441911]: clip_: 1
[ INFO] [1573519993.150403588]: clip_min_height: 0.200000
[ INFO] [1573519993.151369125]: clip_max_height: 5.000000
[ INFO] [1573519993.152273273]: keep_lanes: 0
[ INFO] [1573519993.153210256]: keep_lane_left_distance: 5.000000
[ INFO] [1573519993.154151393]: keep_lane_right_distance: 5.000000
[ INFO] [1573519993.157007388]: cluster_merge_threshold: 1.500000
[ INFO] [1573519993.157040367]: output_frame: world
[ INFO] [1573519993.157952331]: remove_points_upto: 0.000000
[ INFO] [1573519993.158859758]: rm_ground_max_height: 0.200000
[ INFO] [1573519993.159777004]: rm_ground_max_angle: 0.100000
_clustering_thresholds: 0.5 1.1 1.6 2.1 2.6 
_clustering_distances: 15 30 45 60

[YOLOv3 model] Total Inference time: 132.92
[ INFO] [1573692465.648741476]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692465.648815280]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692465.654816654]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.519339    (368,382)-(419,470) WILL BE RENDERED!
[9] element, prob = 0.542692    (1265,357)-(1286,410) WILL BE RENDERED!
[9] element, prob = 0.73251    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.774404    (1173,330)-(1199,390) WILL BE RENDERED!
[9] element, prob = 0.777636    (660,227)-(704,307) WILL BE RENDERED!
[9] element, prob = 0.797869    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.827907    (222,266)-(250,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 141.547
[ INFO] [1573692465.815947144]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692465.816125210]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692465.821551153]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.517651    (1166,328)-(1192,388) WILL BE RENDERED!
[9] element, prob = 0.529321    (1265,357)-(1286,410) WILL BE RENDERED!
[9] element, prob = 0.541512    (369,382)-(420,470) WILL BE RENDERED!
[9] element, prob = 0.718599    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.787882    (660,227)-(704,307) WILL BE RENDERED!
[9] element, prob = 0.805389    (222,266)-(251,339) WILL BE RENDERED!
[9] element, prob = 0.811356    (604,381)-(631,430) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 139.528
[ INFO] [1573692465.979062469]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692465.979147435]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692465.985056132]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.509362    (1265,357)-(1286,410) WILL BE RENDERED!
[9] element, prob = 0.520959    (370,382)-(420,470) WILL BE RENDERED!
[9] element, prob = 0.713559    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.775284    (1173,329)-(1199,390) WILL BE RENDERED!
[9] element, prob = 0.789382    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.806354    (222,266)-(250,339) WILL BE RENDERED!
[9] element, prob = 0.814376    (604,381)-(631,430) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 135.095
[ INFO] [1573692466.141292421]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.141357265]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.147714559]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.505828    (1166,328)-(1192,389) WILL BE RENDERED!
[9] element, prob = 0.509245    (369,383)-(419,471) WILL BE RENDERED!
[9] element, prob = 0.582197    (1264,357)-(1285,410) WILL BE RENDERED!
[9] element, prob = 0.668712    (660,228)-(703,307) WILL BE RENDERED!
[9] element, prob = 0.72905    (989,408)-(1012,444) WILL BE RENDERED!
[9] element, prob = 0.810221    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.824375    (222,266)-(250,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 143.282
[ INFO] [1573692466.311568419]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.311673307]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.317944510]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.531257    (1264,357)-(1285,410) WILL BE RENDERED!
[9] element, prob = 0.537129    (369,383)-(419,471) WILL BE RENDERED!
[9] element, prob = 0.711205    (223,268)-(251,338) WILL BE RENDERED!
[9] element, prob = 0.728396    (989,408)-(1013,443) WILL BE RENDERED!
[9] element, prob = 0.754899    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.764722    (1173,329)-(1199,390) WILL BE RENDERED!
[9] element, prob = 0.802272    (604,381)-(631,430) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 138.735
[ INFO] [1573692466.476747338]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.476849503]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.483104240]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.522163    (369,382)-(419,470) WILL BE RENDERED!
[9] element, prob = 0.727146    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.773133    (1173,330)-(1199,391) WILL BE RENDERED!
[9] element, prob = 0.789589    (660,227)-(703,306) WILL BE RENDERED!
[9] element, prob = 0.80187    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.848182    (223,266)-(251,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 141.283
[ INFO] [1573692466.644343526]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.644397735]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.649761901]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.519377    (369,383)-(420,471) WILL BE RENDERED!
[9] element, prob = 0.730925    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.772681    (1173,329)-(1199,390) WILL BE RENDERED!
[9] element, prob = 0.786392    (660,228)-(704,307) WILL BE RENDERED!
[9] element, prob = 0.790988    (223,266)-(251,339) WILL BE RENDERED!
[9] element, prob = 0.813983    (604,381)-(631,430) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 140.768
[ INFO] [1573692466.811892776]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.811958544]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.817682112]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.525941    (369,382)-(419,470) WILL BE RENDERED!
[9] element, prob = 0.723062    (989,408)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.787405    (1173,329)-(1199,390) WILL BE RENDERED!
[9] element, prob = 0.796122    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.799669    (223,266)-(251,339) WILL BE RENDERED!
[9] element, prob = 0.804626    (604,381)-(631,430) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 137.96
[ INFO] [1573692466.976160838]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692466.976222209]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692466.982404231]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.516538    (1264,357)-(1285,410) WILL BE RENDERED!
[9] element, prob = 0.721421    (988,408)-(1012,444) WILL BE RENDERED!
[9] element, prob = 0.779655    (1173,330)-(1199,391) WILL BE RENDERED!
[9] element, prob = 0.787132    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.800222    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.82265    (222,265)-(251,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 134.363
[ INFO] [1573692467.135230779]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692467.135299774]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692467.142074139]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.506846    (369,382)-(420,470) WILL BE RENDERED!
[9] element, prob = 0.713898    (989,408)-(1013,443) WILL BE RENDERED!
[9] element, prob = 0.788275    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.789782    (1173,330)-(1199,391) WILL BE RENDERED!
[9] element, prob = 0.806017    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.820947    (222,265)-(250,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 134.81
[ INFO] [1573692467.297040782]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692467.297108747]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692467.303166453]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
[9] element, prob = 0.501055    (1264,357)-(1285,410) WILL BE RENDERED!
[9] element, prob = 0.535211    (369,383)-(419,470) WILL BE RENDERED!
[9] element, prob = 0.729431    (988,409)-(1012,444) WILL BE RENDERED!
[9] element, prob = 0.780234    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.781127    (1173,330)-(1199,391) WILL BE RENDERED!
[9] element, prob = 0.798357    (604,381)-(631,431) WILL BE RENDERED!
[9] element, prob = 0.848061    (222,266)-(250,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 200.237
[ INFO] [1573692467.523475888]: published a msg to 'perception/obstacle_detection.'
[ INFO] [1573692467.523549225]: published a msg to 'traffic_light_internal.'
[ INFO] [1573692467.529240893]: obstacle_detection/main.cpp: New frame arrived.
Accepted image input
^C[rviz-4] killing on exit
[traffic_sign_detection_node-2] killing on exit
[obstacle_detection_node-3] killing on exit
[traffic_light_detection_node-1] killing on exit
[9] element, prob = 0.510156    (1166,328)-(1192,389) WILL BE RENDERED!
[9] element, prob = 0.515447    (369,383)-(419,471) WILL BE RENDERED!
[9] element, prob = 0.551537    (1264,357)-(1285,410) WILL BE RENDERED!
[9] element, prob = 0.733814    (989,409)-(1013,444) WILL BE RENDERED!
[9] element, prob = 0.791666    (660,227)-(704,306) WILL BE RENDERED!
[9] element, prob = 0.808993    (604,381)-(630,430) WILL BE RENDERED!
[9] element, prob = 0.820049    (222,266)-(251,339) WILL BE RENDERED!
[YOLOv3 model] Total Inference time: 147.271
[ INFO] [1573692467.693394209]: published a msg to 'perception/obstacle_detection.'
shutting down processing monitor...
... shutting down processing monitor complete
done

better results: running object detection

[[[]{.companion-edit-button-placeholder .edit-button-overlay data-linked-resource-container-id=”1442304” data-linked-resource-id=”1442305” data-template-name=”companionEditIcon” data-source-location=”embedded-attachment”}]

Attachments:

fpga_result.txt (text/plain)\

Document generated by Confluence on Dec 10, 2021 04:01

Atlassian