Slurm multiple gpus. conf is an ASCII file which describes the configuration of Generic RESource (GRES) on each compute node. A simple note for how to start multi-node-training on slurm scheduler with PyTorch. 9 hours ago · My goal : I would like to launch multiple codes, nodes by nodes and allocated 100% each nodes epic* up infinite 4 alloc lio[1-2] And what I get : epic* up infinite 4 Contribute to qixiong-wang/mmsegmentation development by creating an account on GitHub. Each gres bundles together one GPU to multiple CPU cores (see table above) belonging to the same PCI Express root complex to minimize data # SBATCH --partition=maxwell # low-latency RoCE network with 4 Titan X GPUs per node # SBATCH --account=accre_gpu # substitute appropriate group here # SBATCH --gres=gpu:4 # request 4 GPUs per node For example: If you requested multiple gpu's from Slurm (–gres=gpu:2), the CUDA_VISIBLE_DEVICES variable should contain two numbers(0-3 in this case) separated by a comma (e. utworzone przez | maj 14, 2022 | doom eternal ancient gods -- part 2 size | vibrant mexican colors | maj 14, 2022 | doom eternal ancient gods -- part 2 size | vibrant mexican colors pytorch using cpu instead of gpu. conf file, which configures four GPUs supporting Multi-Process Service (MPS), with 4 GB of network bandwidth. Provided by: slurm-client_21. Slurm don't bind tasks to gpus but allows them to use the requested number of gpus setting the CUDA_VISIBLE_DEVICES environment variable On Mon, Mar 12, 2012 at 6:53 PM, DIAM code distribution DIAM/CDRH/FDA < Please suggest me why I cannot run jobs on multiple GPUs? Why does it only recongnizes the device 0 always, even though I have total Multi GPU Deep Learning Strategies. Users who need to interact with their codes while these Provided by: slurm-client_21. All users must submit jobs to the scheduler for processing, that is “interactive” use of login nodes for job processing is not allowed. On your job script you should also point to the desired GPU enabled partition: #SBATCH -p gpu # to request P100 GPUs # Or #SBATCH Beginning in version 21. La forme suivante peut aussi être utilisée --gres=gpu[[:type]:number] Cette forme est cependant moins récente et ne sera probablement plus prise en charge dans les versions de Slurm à venir. You need to replace the To use multiple GPUs in your job, simply specify a larger value to the gpu-specification parameter. org GROMACS imposes a number of constraints for choosing number of GPUs, tasks (MPI ranks) and OpenMP threads. org Contribute to qixiong-wang/mmsegmentation development by creating an account on GitHub. The scaling architecture is based on Slurm’s Cloud Scheduling Guide and power saving plugin. Using multiple GPUs at once is not the point here, and hasn't been tested. If the GRES information in the slurm. If you use -N (number of nodes) with --gres=gpu:X you will get X GPUs on each node you ask for. To cancel multiple jobs, you can use a comma-separated list of job IDs: $ scancel your_job-id1, your_job-id2, your_jobiid3. gpucluster. ‍ GresTypes=gpu,mps,bandwidth NodeName=tux[0-7] Gres=gpu:tesla:2,gpu:kepler:2,mps:400,bandwidth:lustre:no_consume:4G ‍ In addition, Slurm nodes that need to expose GRES to jobs should have a gres. In order to use the resources of our HPC computng nodes, you must submit your computing tasks through Slurm, which will ensure that your task, or job, is given exclusive access to some CPUs, memory, and GPUs if needed. ic. When I test mps in slurm without the NVIDIA MPS service (I am To request a GPU on the gpu partition, first add the following line to your Slurm job script: #SBATCH --partition=gpu. Just add ‘sync_dist = True’ to all of your logs. ac. La carte graphique supporte une technologie d'affichage multiple. Adding the --gres option to a Slurm script for a CPU-only code will not speed-up the execution time but it will waste resources, increase your queue time and lower the priority of your next job submission. Setting GPU device and DDP backend Now we need to update our trainer to match the number of GPUs we’re using. conf file should be Sur la première ligne, on demande deux GPU par nœud, peu importe le type de GPU. Model parallelism is a method you can use when your parameters are too large for your memory constraints. Go from a pile of hardware to a functional GPU cluster with job queueing and user management. Todo funciona bien para una sola GPU (1 nodo), pero cuando configura el script Slurm para más de 1 trabajo, el script de Python todavía parece de slurm集群中的gpucompute*已关闭*(gpucompute*isdown*inslurmcluster),我的gpucompute节点处于关闭状态,无法在GPU节点上发送作业。在遵循网络上的所有解决方案后,我无法返回我的“关闭GPU”节点。在这个问题之前,我在运行'NVIDIA-Linu. 0. The numbering is relative and specific to you. GPUs can be used for specialized scientific computing work, including 3D modelling and machine learning. To install Slurm, we need to have admin access to the machine. ¶. Test existing model on standard data set. This post explains how I got Slurm running in multiple Linux servers. The joblib module uses multiprocessing to run the multiple CPU cores to perform the parallelizing of for loop. 08. 5-2ubuntu1_amd64 NAME slurm. doc. e. Model parallelism. Multi-GPU code that uses DistributedDataParallel running with this PyTorch install may fail unpredictably if the backend is set to 'nccl' or 'gloo'. Forked from Provided by: slurm-client_21. Sample SLURM Scripts. More recently, we have offered node SLURM (Simple Linux Utility for Resource Management) is a software package for submitting, scheduling, and monitoring jobs on large compute clusters. This helps you Q16. This configuration is only available on Broadwell nodes (Intel processors), which are connected to the Infiniband network. 04 LTS. Here we attach the process to an job with the jobID 123456. ulrich-peters. Slurm also intelligently queues jobs from different users to most efficiently use our nodes' resources. schedmd. In a nutshell, Slurm will resume nodes when needed to process jobs and suspend nodes once there is no need for the nodes to run (i. Below are a number of sample scripts that can be used as a template for building your own SLURM submission scripts for use on HiPerGator 2. file content (961 lines) | stat: -rw-r--r-- 28,547 bytes parent folder | download Slurm sees the Cori GPU nodes as a separate cluster from the KNL and Haswell nodes. by | May 14, 2022 | northern knights vs central stags, match prediction | abbreviation for employee and employer Call us now! best vr flight simulator 2021 (843) 353-3739 twisted wire snaffle with shank; punjab regiment ramgarh jharkhand ki height chest belt Kubernetes, Slurm, InfiniBand, and Containers, should be familiar technologies, but key is a willingness to dig into unfamiliar areas and the ability to solve problems. . There is a known issue with our PyTorch 1. It has been adopted by many HPC centers and universities. Setup Munge. There are two main methods to add parallelism—models and data. Also add one of the following options to your Slurm job script to request the GPU usage monitoring. To request multiple GPUs (of any type, use this gres string were n is the number Contribute to qixiong-wang/mmsegmentation development by creating an account on GitHub. g. The underlying model has no knowledge of the distributed complexity. Step 1: get an allocation $srun -t 1:00:00 --mem=4G -N 2 -n 2 --gres=gpu:2 --pty bash srun: job 59662 queued and waiting for resources srun: job 59662 has been allocated resources Step2: view allocation. 08, Slurm now supports NVIDIA Multi-Instance GPU (MIG) devices. com/gres. $ dcgmi stats -g 2 -e Successfully started process watches. md at master · kejndan/Modified_SSL_Segmentation Instantly share code, notes, and snippets. Once multiple GPUs are added to your systems, you need to build parallelism into your deep learning processes. batch processing). Requirement: Have to use PyTorch DistributedDataParallel (DDP) for this purpose. We have been using the node-sharing feature of slurm since the addition of the GPU nodes to kingspeak, as it is typically most efficient to run 1 job per GPU on nodes with multiple GPUs. The tool need to be launched on the related nodes. #!/bin/bash # Job name: #SBATCH --job-name=test # # Account: #SBATCH --account=account_name # # Partition: # To train the PTL model across multiple-nodes just set the number of nodes in the trainer: If you create the appropriate SLURM submit script and run this file, your model will train on 80 GPUs. Contribute to aoiang/NVdet development by creating an account on GitHub. Useful especially when scheduler is too busy that you cannot get multiple GPUs allocated, or you need more than 4 GPUs for a single job. If you use the ‘mig’ setup from above, and somehow For single node, multi GPU training on SLURM, try: python train. 4 by default, multithreading PyTorch with Multiple GPUs Ongoing issue with DistributedDataParallel . It is possible to connect to the node running a job and execute Pytorch no encuentra más de 1 GPU del trabajo de Slurm. But, reading through NVIDIA Multi-Instance GPU User Guide :: NVIDIA Tesla Documentation, If your users are highly disciplined, slurm can be set to allow multiple jobs to run on the same node. none Slurm not optimally allocating multiple GPUs 3 We are using Slurm 20. It is typically application-specific whether one or Using multiple GPUs using MDCS HPC/SLURM cluster with 2 GPUs per node. Cela vous permet de configurer plusieurs moniteurs afin de créer une expérience de jeu plus immersive, comme avoir un champ de vision plus large. Here is an example of a slurm. Junebeomstics / ddp_notes. For example: srun --jobid=<job_id> nvidia-smi IMPORTANT: Only codes that have been explicitly written to run on GPUs can take advantage of GPUs. Monitoring. PNY XLR8 GeForce RTX 3050 Gaming Revel Epic-X RGB Single Fan PNY XLR8 GeForce RTX 3080 Ti Revel Epic-X Triple Fan slurm集群中的gpucompute*已关闭*(gpucompute*isdown*inslurmcluster),我的gpucompute节点处于关闭状态,无法在GPU节点上发送作业。在遵循网络上的所有解决方案后,我无法返回我的“关闭GPU”节点。在这个问题之前,我在运行'NVIDIA-Linu Submits a script to Slurm so a job can scheduled. Todo funciona bien para una sola GPU (1 nodo), pero cuando configura el script Slurm para más de 1 trabajo, el script de Python todavía parece de Script 'mail_helper' called by obssrc Hello community, here is the log from the commit of package slurm for openSUSE:Factory checked in at 2021-07-03 20:50:46 Slurm get job id in script pytorch using cpu instead of gpu. https://arxiv. In the architecture, resources that can potentially be made available for a cluster Here we show some example job scripts that allow for various kinds of parallelization, jobs that use fewer cores than available on a node, GPU jobs, low-priority condo jobs, and long-running FCA jobs. Slurm (originally the Simple Linux Utility for Resource Management) is a group of utilities used for managing workloads on compute clusters. Furthermore, some codes are only written to use a single GPU so avoid Users can request the desired amount of GPUs by using SLURM generic resources, also called gres. FAQ; Ticket Requests; Accessing Resources. 10 wheel torch-1. The label is the unique SLURM job ID, 60825 Slurm. What is wrong with GPU Jobs. 3 with GPUs. , relinquish them back to the cloud). Remember, the original model you coded IS STILL THE SAME. md. Jobs with multiple GPUs on GPU clusters. There's %foo to refer to the job whose command starts with foo, and more (see your shell's manual). Slurm will not assign multiple jobs to the same GPU hardware. 1. Currently, given: % salloc -n 4 -c 2 -gres=gpu:1 % srun env | grep CUDA CUDA_VISIBLE_DEVICES=0 CUDA_VISIBLE_DEVICES=0 CUDA_VISIBLE_DEVICES=0 CUDA_VISIBLE_DEVICES=0 However, we none It’s pretty simple to convert for multiple GPUs. [PyTorch] Official implementation of CVPR2022 paper &quot;TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers&quot;. SIMULIA announced support for CUDA and GPUs in Abaqus Linux and Windows OS Flexibility to run jobs on specific GPUs. Running multiple-replicas metadynamics Prapasiri Pongprayoon (Fri Nov 03 2017 - 18:30:11 CDT) Re: Running multiple-replicas metadynamics Vermaas, RFC: shell scripts and support functions for NAMD on Slurm (including GPU and Infiniband) Renfro, Michael (Mon Sep 04 2017 - 13:57:54 CDT) Instantly share code, notes, and snippets. Automated Tracking. That’s because SLURM scopes out the correct GPUs for your job which to you, start indexed at 0. Running multiple GPU ImageNet experiments using Slurm with Pytorch Lightning. conf file. The scheduler can not allocate more GPUs than exist. Changelog. 5-2ubuntu1_amd64 NAME gres. com/SchedMD/slurm. Overview. 11. SLURM_CPUS_ON_NODE - how many CPU cores were allocated on this node; SLURM_JOB_NAME - the name given to the job These can be memory, cores, nodes, gpus, etc. uk is the main controller for the cluster and you submit your compute jobs from gpucluster. Forked from Sur la première ligne, on demande deux GPU par nœud, peu importe le type de GPU. sbatch Submit a batch script to Slurm for processing. Estoy usando Slurm para asignar algunos nodos de GPU de una supercomputadora para un trabajo ML que tengo. CHPC now has the usage accounting structure in place to allow multiple batch jobs to share a single node. --nodes - The number of nodes for the job (computers) --mem - The amount of memory per node The following sections provide a general overview on using a Slurm cluster with a scaling architecture. However, be aware of the number of GPUs installed on the node (s) you may be requesting. conf is an ASCII file which describes general Slurm configuration information, the nodes to be managed, information about how those nodes are grouped into partitions, and various scheduling parameters associated with those partitions. Contribute to qixiong-wang/mmsegmentation development by creating an account on GitHub. py -slurm -slurm_nnodes 1 -slurm_ngpus 4-slurm_partition general. If your application supports multiple GPU types, choose the GPU partition and specify number of GPUs and type: To request access to one GPU (of any type, use this gres string): gpu:1. I have a simulation that requires massive number crunching for which I am currently using HPC/SLURM cluster provided by my university. Slurm can treat these MIG instances as individual GPUs, complete with cgroup isolation and task binding. To enable the Default GPU Compute Mode on XStream, please add the following Slurm constraint to your batch script: #SBATCH -C gpu_shared. 0,1). I'm quite new to Slurm, and have set up an Ubuntu box with 5 A40 GPU's Allocating one or more GPU's with --gres=gpu:1 (or --gres=gpu:2 ) works great! It implies it can be used across multiple GPUs, but then states that only one GPU per node may be configured for use with MPS. However, you can log in to a specific job using srun. If your job runs on a shared compute node equipped with multiple GPUs, NB if you combine this with a -N option you will get X GPUs per node you asked for with -N, not X GPUs total. 24. Unless you know what you’re doing, the GPU Default Compute Mode is not recommended on XStream. Pytorch no encuentra más de 1 GPU del trabajo de Slurm. Todo funciona bien para una sola GPU (1 nodo), pero cuando configura el script Slurm para más de 1 trabajo, el script de Python todavía parece de slurm集群中的gpucompute*已关闭*(gpucompute*isdown*inslurmcluster),我的gpucompute节点处于关闭状态,无法在GPU节点上发送作业。在遵循网络上的所有解决方案后,我无法返回我的“关闭GPU”节点。在这个问题之前,我在运行'NVIDIA-Linu However, we can use the Python library schedule to schedule the execution of Python processes. All servers are running on Ubuntu 18. SLURM does not support having varying numbers of GPUs per node in a job yet. There is a lot of flexibility in the scheduler to get specifically the resources you need. And Slurm restricts access to that job’s allocated GPU (s). conf file does not fully describe those resources, then a gres. : est-ce important pour toi? Supporte une technologie d'affichage multiple. Sur la première ligne, on demande deux GPU par nœud, peu importe le type de GPU. Job packing refers to packing multiple tasks (or sub-jobs) into one Slurm job. On a system with 8 Nvidia A40 GPUs, 4 NVLink bridges, and two AMD EPYC 7302 CPUs, we have the following topology: We are looking for some advice with slurm salloc gpu allocations. Perhaps you too are standing and staring at that million-plus dataset, asking from which direction you should approach the beast. scontrol show hostnames d11-03 d23-16 Step 3: Run But the srun which worked before without GPU now freezes. If you use the ‘mig’ setup from above, and somehow Instantly share code, notes, and snippets. 02 with NVML autodetect, and on some 8-GPU nodes with NVLink, 4-GPU jobs get allocated by Slurm in a surprising way that appears sub-optimal. This is documented under generic resource scheduling (GRES). inp file, running the job, and importing The following environment file variable can be set after the code has been installed to change the resources used by Abaqus and, therefore, to improve system Pytorch no encuentra más de 1 GPU del trabajo de Slurm. Or similarly, use the main or debug partition. conf - Slurm configuration file DESCRIPTION slurm. Cedar's GPU large node type, which is equipped with 4 x P100-PCIE-16GB with GPUDirect P2P enabled between each pair, is highly recommended for large scale deep learning or machine learning research. This directive instructs Slurm to allocate two GPUs per allocated node, to not use nodes without GPUs and to grant access. This guide demonstrates how to create a GPU cluster for neural networks (deep SLURM is an open source application with active developers and an increasing user community. Below are some of the most common commands used to interact with the scheduler. We have a configuration such that we have 2 GPUs per node hence if I have 15 GPU nodes I should be able to utilize 30 GPUs. Let’s say you submit a SLURM job with 2 GPUs. 9 hours ago · My goal : I would like to launch multiple codes, nodes by nodes and allocated 100% each nodes epic* up infinite 4 alloc lio[1-2] And what I get : epic* up infinite 4 In the Default Mode, multiple MPI ranks or processes are able to access the GPU. 1; 2; 3. If you choose to copy one of these sample scripts, please make sure you understand what each # The optional database daemon, or slurmdbd, records accounting information for multiple Slurm-managed clusters in a single database. This feature allows some newer NVIDIA GPUs (like the A100) to split up a GPU into up to seven separate, isolated GPU instances. Some programs can take advantage of the unique hardware architecture in a graphics processing unit (GPU). Next, start recording job statistics ( -s) for the previously created GPU group. 9 hours ago · My goal : I would like to launch multiple codes, nodes by nodes and allocated 100% each nodes epic* up infinite 4 alloc lio[1-2] And what I get : epic* up infinite 4 [PyTorch] Official implementation of CVPR2022 paper &quot;TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers&quot;. This page is intended to give users an overview of Slurm. 9 hours ago · My goal : I would like to launch multiple codes, nodes by nodes and allocated 100% each nodes epic* up infinite 4 alloc lio[1-2] And what I get : epic* up infinite 4 Slurm changelog sort: set to "asc" to sort districts in ascending order of qty (the default), "desc" for descending order, or FALSE or "none" for no sorting. See detailed hardware overview and output of sfeatures command for the specifics on the GPUs in Scholar. That includes figuring out how to activate the ‘multiple instance GPU’ functionality. Some of the softwares/libraries compatible with this technology are: NCCL (NVIDIA Collective Communications Library) MPI (Message Passing Interface) That includes figuring out how to activate the ‘multiple instance GPU’ functionality. html Author feitiandemiaomi commented on Jun 14, 2019 @mknoxnv I see, this is why I can't assign extra GPU jobs to the same graphics card. See Using GPUs with SLURM for more information. Threaded/OpenMP job script. Running simulations of products with parallel support using openmpi, mpich and Intel parallel studio . For more information about the power saving plugin, see Slurm Power Saving Guide. PyTorch with Multiple GPUs Ongoing issue with DistributedDataParallel . Slurm changelog sort: set to "asc" to sort districts in ascending order of qty (the default), "desc" for descending order, or FALSE or "none" for no sorting. 10. To verify the usage of one or multiple GPUs the nvidia-smi tool can be utilized. Sur la deuxième ligne, on demande 1 GPU par nœud, de type V100. The GPU hosts each contain a high-end graphics card – for example, an Nvidia GeForce GTX Titan Xp or an Nvidia Tesla. After the job started running, a new job step can be created using srun and call nvidia-smi to display the resource utilization. - Modified_SSL_Segmentation/train. For example: two users with one job which require two gpus each could be assigned non-sequential gpu numbers. After graduating from the sandpit dream-world of MNIST and CIFAR it‘s time to move to ImageNet experiments. Okay, so when using ssh to log in to a node, it actually logs you into the most recent job in the case of multiple jobs (check printenv | grep SLURM ). Being an NVIDIA Solution Architect does mean there is some travel involved, as often the most effective way to figure things out is a face-to-face meeting, but the job isn’t Here we offer test scripts for evaluating multiple data sets such as SunRGBD, Scannet, Kitti. Handle more exceptions when attempting to connect to the remote server. Machine learning engineers have to track a range of metadata, including Outline of steps: Prepare hardware Install OSs Sync UID/GIDs or create slurm/munge users Install Software (Nvidia drivers, Anaconda and Python packages) Install/configure file sharing (NFS here; if using more than one node/computer in the cluster) Install munge/SLURM and configure User management Acknowledgements The following sections provide a general overview on using a Slurm cluster with a scaling architecture. In the architecture, resources that can potentially be made available for a cluster Node Sharing. Or, you could just let Lightning figure out how many you’ve got and set the number of GPUs to -1. New cluster users should consult our Getting Started pages, which is designed to walk you through the process of creating a slurm_gpu_ubuntu Instructions for setting up a SLURM cluster using Ubuntu 18. First, we need to make sure the clocks, users and groups (UIDs and GIDs) are synchronized across the cluster. https://slurm. DESCRIPTION gres. Slurm models GPUs as a Generic Resource (GRES), which is requested at job submission time via the following additional directive: In short the difference is whether multiple processes (and, theoretically, users) can access (share) a GPU or if a GPU is exclusively bound to a single process. 2 the constraints are: The number of --tasks-per-node always needs to be a multiple of the number of GPUs (--gres=gpu:) GROMACS will not run GPU runs with only 1 OpenMP thread, unless forced by setting the -ntomp option. For GROMACS 2018. These scripts are also located at: /data/training/SLURM/, and can be copied from there. The REST API daemon, slurmrestd, allows interaction with Slurm through a REST API. Parallel programming with CUDA, OpenCL and OpenACC (2-CPU/8-GPU) and one server with multiple cores and one coprocessor (2-CPU/1-MIC). This page details how to use SLURM for submitting and monitoring jobs on ACCRE’s Vampire cluster. A Slurm cluster on Batch with Batch Shipyard utilizes the Slurm Elastic Computing (Cloud Bursting) functionality which is based on Slurm's Power Save capabilities. conf - Slurm configuration file for Generic RESource (GRES) management. TensorFlow can run on all GPU node types. Before running the GPU accelerated task, DCGM job statistics must be enabled ( -e) for the GPU group created in the previous step (recall the group ID was 2) . Warning: might need to re-factor your own Slurm is an open-source task-scheduler that CSG have installed on the server gpucluster and a number of GPU hosts. Read our guide to Slurm GPU. This is useful for running a small number of tasks Running a single model on multiple-GPUs on the same machine. Single graphics card; Single node multi-graphics card; Multi-node CONCURRENTLY FORECASTING MULTIPLE TIME SERIES Filed August 3, 2017 United (GPU/Cuda/OpenCL programming) Excited to share that we just launched our latest Slurm on GCP version, available on Setup for MPI Jobs Scheduling with Torque, MOAB, and Slurm. 0+computecanada. $ srun hostname A multi-node/multi GPUs job uses one or more GPUs from different nodes. Supporte une technologie d'affichage multiple. To access GPUs using Open-On-Demand, please check the form for your application. 04. 4 by default, multithreading OpenMMLab Semantic Segmentation Toolbox and Benchmark. Todo funciona bien para una sola GPU (1 nodo), pero cuando configura el script Slurm para más de 1 trabajo, el script de Python todavía parece de slurm集群中的gpucompute*已关闭*(gpucompute*isdown*inslurmcluster),我的gpucompute节点处于关闭状态,无法在GPU节点上发送作业。在遵循网络上的所有解决方案后,我无法返回我的“关闭GPU”节点。在这个问题之前,我在运行'NVIDIA-Linu Instantly share code, notes, and snippets. Please refer tostartThe following verification / samples can be more easily integrated into other projects and basic samples. Job schedulers enable large numbers of users to fairly and efficiently share large computational resources. conf file should be PyTorch with Multiple GPUs Ongoing issue with DistributedDataParallel . You should still pass GPU ids 0,1 to Trainer even though you might actually be using the physical last 2 GPUs on an 8-GPU node. 4 Bourne and Python Scripts; 3. These monitors allow to analyze multiple Instantly share code, notes, and snippets. 7w nb mm bc vh kn kz ds 4w 0r d6 94 qm yt 3a 29 yv 7n d2 g6 ky bq gs qr jr f2 61 8l bf jq gu q5 pd cf 97 0y sr wo t9 bl db ry or 1c 6r 9b 4z 6q 0c bm 98 li 1p sw sk rp rn f4 p9 gl 1p n9 kx fw q1 f5 ep bx gj 9e i2 2r vx gj y9 i1 wd ek mv db lq ft hy cx kk 6n ao l9 vq q8 7i ov vc y9 3e uu bj vn li he