vSphere Client on openSUSE 42.2

Posted: April 10, 2017 in linux
Tags: ,

I needed vSphere client on linux, but vmware only builds a Windows version. Here is my work-around:

First, install vSphere Client via wine. I personally used vSphere Client (and server) 5.1.

WINEARCH=win32 WINEPREFIX=$HOME/.vmware-client ./winetricks msxml3 dotnet35sp1 vcrun2005 vcrun2008 vcrun2010
WINEARCH=win32 WINEPREFIX=$HOME/.vmware-client wine VMware-viclient-all-5.1.0-2306356.exe
When you get the hcmon install failure, copy the entire contents of your wine bottle to a tmp directory, complete the installation (says it failed), then mv the contents back.
cp $HOME/.vmware-client $HOME/.vmware-client2

rm -rf $HOME/.vmware-client
mv $HOME/.vmware-client2 $HOME/.vmware-client

Now you can run the vSphere Client with:
WINEARCH=win32 WINEPREFIX=$HOME/.vmware-client wine ~/.vmware-client/drive_c/Program\ Files/VMware/Infrastructure/Virtual\ Infrastructure\ Client/Launcher/VpxClient.exe

The biggest drawback is that the console doesn’t work, so install VMware Remote Console.
The remote console can connect to a vSphere server and provide the console functionality that’s broken in the client. Just provide it the host url, username, etc on the command line:

> /usr/bin/vmrc –help
vmrc [OPTION…]

Help Options:
-h, –help Show help options

Application Options:
-v, –version Display the program version
-X, –fullscreen Start in fullscreen mode
-M, –moid=moid A managed object id indicating the VM to connect to
-U, –user=username Username used to authenticate to the remote host
-P, –password=password Password used to authenticate to the remote host
-D, –datacenter=datacenter Datacenter containing the VM to open
-H, –host=host:port Remote host containing VMs you wish to access

Authors: David Mulder, Curtis Welborn


This paper describes the implementation of a garbage collector as an undergraduate research project. The garbage collector is a continuation of a project where an Assembler, Virtual Machine and Compiler were implemented as a capstone project. The project required modifying the compiler to allocate memory compatible with a mark and sweep algorithm, and adding the mark and sweep algorithm to the virtual machine. Computer Science faculty should take note that this was all completed by an undergraduate student within a year’s time, and that such challenges can reasonably be accomplished by undergraduate seniors.


Challenges of the nature described in this paper are generally reserved for graduate students, and are considered outside the grasp of undergraduates. Computer Science faculty and students alike will be interested to note that the preceding project was completed entirely by an undergraduate senior. It is also interesting to note that the project was completed by an average student of little academic achievement, and that a Compiler, Assembler and Multi-Processed Virtual Machine with Garbage Collection were written within a year’s time.

As part of an undergraduate capstone, an Assembler, Virtual Machine and Compiler were implemented. The two-pass Compiler performs Lexical and Syntax analysis in the first pass, and Semantic analysis and Intermediate code generation in the second pass. Using Intermediate code as input, the Compiler then generates target code (assembly) that can be fed to the Assembler to generate byte-code. The byte-code can then be loaded into the Virtual Machine for execution [1]. Through independent study, a garbage collector was added to the virtual machine, which included extensive changes to the compiler.

The compiler had to be modified to place by-reference parameters onto the run-time stack first. An additional parameter is also added that counts the number of by-reference parameters. The counter is needed by the Mark and Sweep algorithm to determine the location of the by-reference parameters within an Activation Record.

To support the mark and sweep garbage collection algorithm, the virtual machine had to be modified to allocate memory from a list of available blocks. The mark and sweep algorithm is triggered when a call to allocate memory detects no free blocks. In the mark phase of the algorithm, the run-time stack is traversed searching for points that reference blocks allocated on the heap. Any block of memory reachable from the run-time stack must be marked as in use. During the sweep phase of the algorithm, the heap is searched looking for any blocks not marked as in use during the mark phase.
Screenshot from 2015-10-09 13:18:55


The compiler was originally written to pass parameters to a function call via an activation record in the order they were written in the source language (a language called KXI, which is similar to java). It was necessary for the compiler to segregate between by-reference and by-value parameters. The mark phase of the algorithm must know the location of every by-reference parameter within a function calls’ activation record. See the ordering of variables in the current Activation Record of Figure 1. Because the variables are segregated, references are easily located based on offsets. For example, the first reference is located by an offset of 4*sizeof(int) from the base of the activation record (the return address, previous activation record pointer and reference counters are all integers), and the second reference is offset 5*sizeof(int) from the base.

The mark phase of the algorithm needed a special field inserted in each activation record that counts the number of by-reference parameters. This field was added in the activation record in such a way that the mark phase could iterate over each by-reference parameter and set the mark bit in the corresponding block for each object allocated on the heap. The field is referred to as the Reference Counter in Figure 1. The reference counter in this activation record tells us that there are 2 references. If we decremented the reference counter to 1, for example, the second reference on the stack would be interpreted as an integer.


In order to make space allocation more efficient, the heap was separated into large and small blocks. Bit vectors were used to keep track of which blocks are allocated on the heap.

An instruction was added to the virtual machine for allocating memory. Prior to the instruction, memory allocation consisted of just moving a pointer within the heap. The new allocation instruction calls the mark and sweep algorithm. If there is space available on the heap, the instruction returns a pointer to that block and marks the block as unavailable within one of the vectors that tracks all blocks in the heap.

If no available space is found, garbage collection is started. The algorithm must calculate the location of the activation record for the current function call then calculates the offset to the by-reference counter field in the activation record. Now having the number of pass by-references parameters in the current activation record, the algorithm can calculate the offset to each allocated block on the heap and set its mark bit to in use.

The algorithm must recursively follow references allocated inside of each block. This was achieved by organizing objects within a block in a similar manner to how function calls are organized in an activation record. In this way, lists, trees and even recursive data structures allocated on the heap can all be traversed and marked. In Figure 1, the mark phase will follow all references inside of Small Block A, so Small Block B is also marked.

Once all objects (blocks) and descendant objects have been marked, the algorithm calculates the location of the previous activation record. The same process of following references and marking objects proceeds for each activation record until all function calls on the run-time stack have been searched.

The sweep phase of the algorithm now iterates over the entire heap, checking the mark bit. If the mark bit is set (the block is in use), it clears the bit and moves on. This means that the block has a live reference to it which originated in an activation record that is currently on the run-time stack. Blocks A, B and D in Figure 1 have references pointing to them. These blocks will be un-marked and will remain allocated.

If the mark bit is not set, the algorithm clears the relevant marker in the vector of available blocks, freeing the block for reuse (See Small Block C in Figure 1) [2]. This allocated block will be freed during the sweep phase because it has no references pointing to it on the run-time stack.


This method of garbage collection is effective, but did prove to be inefficient. Because the algorithm isn’t activated until there is no remaining free space, the algorithm isn’t suitable for real time applications. The algorithm could be modified to operate incrementally, but it would still cause an occasional lag. These are known problems of garbage collection.

The greatest achievement of this project was the recognition of what can be accomplished by undergraduate seniors. Computer Science faculty should recognize that computing projects of this caliber can reasonably be expected in an undergraduate senior project course.


The primary author has started work on an hp-ux pa-risc virtual machine. The first obstacle will be setting up the correct environment, based on descriptions in the pa-risc specifications. The second will be translating the pseudo code in the specification into C. A compiler/translator will be written to automatically convert the specification pseudo code into C.

A significant part of the project will be writing the loader, since it will need to include things such as run time linking. Ideally, the virtual machine will run at boot time and will include a boot loader. This would allow pa-risc software to run on virtually any hardware.


[1] Mulder, D., Welborn, C., Lessons in converting from python to c++, Journal of Computing Sciences in Colleges, 29(2), 49-57, December 2013, http://dl.acm.org/citation.cfm?id=253542
[2] Jones, R., Lins, R. D., Garbage collection: Algorithms for automatic dynamic memory management, West Sussex, England

© CCSC, (2014). This is the author’s version of the work. It is posted here by permission of CCSC for your personal use. Not for redistribution. The definitive version was published in The Journal of Computing Sciences in Colleges, {volume 30, number 2, December 2014}, http://dl.acm.org/.

Here’s an alternative to applying Configuration Profiles in OSX without using an MDM client. Profiles are deployed using Group Policy over SMB, so you don’t have to open APN ports to Apple.
QAS is an AD bridge tool for unix/linux systems (including mac) that also provides Group Policy support. You can view more details here.

QAS Group Policy lets you specify Group Policy settings inside the Group Policy Management Editor, the same way you’d apply settings for a Windows host.
Screenshot from 2015-10-08 14:48:40It works similar to Apple’s Profile Manager.

Screenshot from 2015-10-08 14:54:54

You can also create custom profiles by writing preference manifests. The preference manifests are converted to Configuration Profiles before they’re applied on the OSX host.

On the OSX host, settings are retrieved from Group Policy, and installed as Configuration Profiles.

Screenshot from 2015-10-08 15:22:01

My new favorite corporate email solution is davmail + geary + california in gnome-shell.

Geary is still a little buggy (version 0.8.3), but I love how light weight it is, while still doing (most of) what I need it to. It really needs html signature support, but that’s the only thing missing that I really use.

Davmail appears to be very stable. I run it in server mode on startup with an init script.

Now all I need is a decent calendar solution. The new gnome app California appears to be the best bet. It’s very buggy in version 0.2. My biggest issue is that overlapping events aren’t handled well. I’m hoping they’ve got that worked out in 0.4.

It feels more fluid using native gnome-shell apps for my corporate email and calendar. Thanks Yorba and davmail!

So, I just reinstalled openSUSE (because the new DEFAULT btrfs borked my system, wont go into that today), and my wifi isn’t working.

Sounds similar to issues described here:

Just thought I’d share how I got things up and running.

First off, here were the symptoms:
1. Gnome network manager indicated that the firmware was not installed (even though this is supposed to be included with the kernel now).
2. # dmesg | grep firmware
[ 19.764863] ieee80211 phy0: brcmsmac: fail to load firmware brcm/bcm43xx-0.fw
3. l /lib/firmware/ # (the brcm directory is completely MISSING)
total 28
drwxr-xr-x 6 root root 4096 Apr 7 09:54 ./
drwxr-xr-x 13 root root 4096 Apr 7 09:53 ../
drwxr-xr-x 31 root root 4096 Apr 6 16:52 3.16.6-2-desktop/
drwxr-xr-x 31 root root 4096 Apr 7 09:54 3.16.7-7-desktop/
-rw-r–r– 1 root root 53 Sep 25 2014 E-CARD.cis
drwxr-xr-x 2 root root 4096 Apr 7 09:52 amd-ucode/
drwxr-xr-x 2 root root 4096 Apr 7 09:53 intel-ucode/

To get it working…
1. Download the kernel-firmware package:
2. Extract the firmware (installing the package would probably work too).
3. cp -r /home/dmulder/Downloads/kernel-firmware-20141122git-5.1.noarch/lib/firmware/brcm /lib/firmware/
4. modprobe bcma

Now that I stop and think about it…
sudo zypper in kernel-firmware
probably would have fixed it.

Simple Browser Project

Posted: March 10, 2015 in linux, netflix
Tags: , ,

I’ve been looking for a good way to access my corporate email on my linux (opensuse) laptop. Evolution is pretty good, but the evolution-ews plugin is REALLY buggy. The connection was dropping every few minutes for me. The user interface also feels too cluttered for what I’m trying to do. So, I decided to try a different approach.

I wrote a simple python based webkit browser to modify the look and feel of owa to make it more like a desktop app.

You can access the source code here:


Or you can install the opensuse package here:


I also plan to use it to play Netflix on my mythtv box. It seems like I should be able to modify the css styling to make the summaries bigger on the page, etc.

Screenshot from 2015-03-10 10:20:02

rgdb Remote debugging

Posted: July 8, 2014 in gdb, linux
Tags: , , ,

Check out the project I’ve been working on in github.
I frequently have to debug C/C++ code from the command line, but I have separate build machines because I build on multiple architectures and platforms. So, I wrote this python script for remote debugging.
All it does is open up an ssh connection (using python paramiko) and connects to gdb on the build machine. It then parses through the output using regular expressions and opens the source code on your local machine for debugging. As you step through the code, the line of code is underlined and centered in the code window.
I also added a useful (for my work) feature which allows you to get the tcpdump while executing a particular line of code. It then opens the tcpdump on your local machine in wireshark.