cluster-computing

问题 We are looking for some advice with slurm salloc gpu allocations. 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 desire more than just device 0 to be used. Is there a way to specify an salloc with srun/mpirun to get the following? CUDA_VISIBLE_DEVICES=0 CUDA_VISIBLE_DEVICES=1 CUDA_VISIBLE_DEVICES=2 CUDA_VISIBLE_DEVICES=3 This is desired such that each task gets 1

问题 We are looking for some advice with slurm salloc gpu allocations. 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 desire more than just device 0 to be used. Is there a way to specify an salloc with srun/mpirun to get the following? CUDA_VISIBLE_DEVICES=0 CUDA_VISIBLE_DEVICES=1 CUDA_VISIBLE_DEVICES=2 CUDA_VISIBLE_DEVICES=3 This is desired such that each task gets 1

问题 In SGE/PBS, I can submit binary executables to the cluster just like I would locally. For example: qsub -b y -cwd echo hello would submit a job named echo, which writes the word "hello" to its output file. How can I submit a similar job to SLURM. It expects the file to have a hash-bang interpreter on the first line. On SLURM I get $ sbatch echo hello sbatch: error: This does not look like a batch script. The first sbatch: error: line must start with #! followed by the path to an interpreter.

问题 I am creating a clustermap with the following code. import numpy as np import pandas as pd import seaborn as sns all_net_names = ['early_vis', 'face', 'motion', 'scene', 'scene', 'scene', 'dmn', 'dmn', 'dmn', 'dmn', 'dmn', 'dmn', 'reward', 'reward', 'reward', 'reward', 'reward', 'ofc', 'ofc', 'ofc', 'ofc'] roi_names = ['E', 'F', 'M', 'S1', 'S2', 'S3', 'D1', 'D2', 'D3', 'D4', 'D5', 'D6', 'R1', 'R2', 'R3', 'R4', 'R5','O1', 'O2', 'O3', 'O4'] n_roi = len(roi_names) M = np.random.rand(n_roi, n_roi

问题 I am creating a clustermap with the following code. import numpy as np import pandas as pd import seaborn as sns all_net_names = ['early_vis', 'face', 'motion', 'scene', 'scene', 'scene', 'dmn', 'dmn', 'dmn', 'dmn', 'dmn', 'dmn', 'reward', 'reward', 'reward', 'reward', 'reward', 'ofc', 'ofc', 'ofc', 'ofc'] roi_names = ['E', 'F', 'M', 'S1', 'S2', 'S3', 'D1', 'D2', 'D3', 'D4', 'D5', 'D6', 'R1', 'R2', 'R3', 'R4', 'R5','O1', 'O2', 'O3', 'O4'] n_roi = len(roi_names) M = np.random.rand(n_roi, n_roi

问题 I have a three php-fpm servers, and a one nginx server, where I want to loadbalance php-fpm using nginx server. php-fpm server1 - 192.168.10.31 php-fpm server2 - 192.168.10.32 php-fpm server3 - 192.168.10.33 nginx - server - 192.168.10.12 My Configuration on nginx server was; upstream php_backend { server 192.168.10.31:9000; server 192.168.10.32:9000; server 192.168.10.33:9000; } location ~ \.php$ { fastcgi_pass php_backend; } But my problem is, where should I define the webroot [ root /path

问题 I have a three php-fpm servers, and a one nginx server, where I want to loadbalance php-fpm using nginx server. php-fpm server1 - 192.168.10.31 php-fpm server2 - 192.168.10.32 php-fpm server3 - 192.168.10.33 nginx - server - 192.168.10.12 My Configuration on nginx server was; upstream php_backend { server 192.168.10.31:9000; server 192.168.10.32:9000; server 192.168.10.33:9000; } location ~ \.php$ { fastcgi_pass php_backend; } But my problem is, where should I define the webroot [ root /path

问题 With a replicating mysql master to master database with innodb engine, if one transaction were to initiate on database A will that row lock for database B until the transaction has been committed? 回答1: The master getting the first transaction is completely separate from the second master and they communicate through a binary log. https://dev.mysql.com/doc/refman/5.7/en/replication-formats.html In the case of something requiring a transaction, then the actual statements are not written to the

问题 Using MATLAB and trying to use a computer cluster to perform 100 repetitions of certain calculation with inherent stochastic nature. Each of those repetitions should include the same code, but with different random seed. It seems that rng('shuffle') recommended by documentation may not achieve this if all jobs start running at the same time (on different machines) as the seed used is an integer which seems to be initialized from time (it is monotonously increasing, seems like precision of

问题 I'm trying to make the health of my cluster green. According to the following elasticsearch documentation: When you add more nodes to a cluster, it automatically allocates replica shards. When all primary and replica shards are active, the cluster state changes to green. source: https://www.elastic.co/guide/en/elasticsearch/reference/current/add-elasticsearch-nodes.html So I created 2 elasticsearch instances with the following configuration files: # Config File 1 cluster.name : PL node.name :