This gist is an implementation of http://sirile.github.io/2015/05/18/using-haproxy-and-consul-for-dynamic-service-discovery-on-docker.html on top of Docker Machine and Docker Swarm.
| Producer | |
| Setup | |
| bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test-rep-one --partitions 6 --replication-factor 1 | |
| bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test --partitions 6 --replication-factor 3 | |
| Single thread, no replication | |
| bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test7 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196 |
| // This is free and unencumbered software released into the public domain. | |
| // | |
| // Anyone is free to copy, modify, publish, use, compile, sell, or | |
| // distribute this software, either in source code form or as a compiled | |
| // binary, for any purpose, commercial or non-commercial, and by any | |
| // means. | |
| // | |
| // In jurisdictions that recognize copyright laws, the author or authors | |
| // of this software dedicate any and all copyright interest in the | |
| // software to the public domain. We make this dedication for the benefit |
| #!/bin/bash | |
| # Cisco Anyconnect CSD wrapper for OpenConnect | |
| # Enter your vpn host here | |
| CSD_HOSTNAME= | |
| if [[ -z ${CSD_HOSTNAME} ]] | |
| then | |
| echo "Define CSD_HOSTNAME with vpn-host in script text. Exiting." | |
| exit 1 | |
| fi |
| /* | |
| * Parallel bitonic sort using CUDA. | |
| * Compile with | |
| * nvcc -arch=sm_11 bitonic_sort.cu | |
| * Based on http://www.tools-of-computing.com/tc/CS/Sorts/bitonic_sort.htm | |
| * License: BSD 3 | |
| */ | |
| #include <stdlib.h> | |
| #include <stdio.h> |
| import kafka.server.KafkaConfig; | |
| import kafka.server.KafkaServer; | |
| import java.io.File; | |
| import java.io.FileNotFoundException; | |
| import java.util.ArrayList; | |
| import java.util.Collections; | |
| import java.util.List; | |
| import java.util.Properties; |
| package org.prokyon.management.bitbucket_cloner; | |
| import com.google.common.base.CaseFormat; | |
| import com.mashape.unirest.http.HttpResponse; | |
| import com.mashape.unirest.http.JsonNode; | |
| import com.mashape.unirest.http.Unirest; | |
| import com.mashape.unirest.http.exceptions.UnirestException; | |
| import org.apache.logging.log4j.LogManager; | |
| import org.apache.logging.log4j.Logger; | |
| import org.eclipse.jgit.api.Git; |
| #!/bin/bash | |
| #title :mkscript.sh | |
| #description :This script will make a header for a bash script. | |
| #author :bgw | |
| #date :20111101 | |
| #version :0.4 | |
| #usage :bash mkscript.sh | |
| #notes :Install Vim and Emacs to use this script. | |
| #bash_version :4.1.5(1)-release | |
| #============================================================================== |
Probably the most straight forward way to start generating Point Clouds from a set of pictures.
VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.
For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]
Probably the most straight forward way to start generating Point Clouds from a set of pictures.
VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.
For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]