Archive for March, 2011

Massive Data Access Library

Today I got introduced to Massive.  Massive is a data access library written by @robconery.  My co workers @jaymed and @mgroves introduced me to it, and I’ll admit I was somewhat reluctant to give it a shot.  I’m normally of the opinion that the simplest DAL is just pure simple SqlCommands, SqlConnections and a stored procedure call.  However after using Massive for a few hours, I’m really excited about this new tool in my tool chest.  Of course massive has been out for a while, I’m quite slow to the party sometimes.

Massive is great though, I love how in a single line of code I can have data back.  Alternatively I can update the table, or run any other query that I want.  This library if it did nothing else makes integration testing a breeze.  Usually for my tests I prefer to stub out a DAL repository via the interface/repository pattern.  The tests get a FakeSomethingRepository to use that uses List<TheObject> as its in memory store.  What I love about massive is that my unit tests which are really simple because they can test DataRepository.SomeList  can quickly become Integration tests with almost no additional complexity.  For me that’s Huge.  I’m trying a new thing, and that’s not to check in any code that doesn’t have full unit test coverage and Massive is making that happen in a Massive way.  (couldn’t resist)

I’m still learning about these Dynamic things, but a bit of learning never hurt anyone and I know @mgroves will help me out when I get confused.

@robconery If we ever meet, I owe you a beer! Massive is awesome!

If you’re not familiar with Massive, I urge you to check it out here.

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P90X First Day

Started my first day of p90X today!  I’m doing the lean track first, I’ll then work though the classic and then maybe the Double or Dual track if I’m really brave.  Its kind of rough getting up earlier so we can work out in the morning but its going to be well worth it in the end.  Today’s workout was core synergistics.  Tomorrow is Cardio X.  I won’t blog after every one, but every so often.  So far my only complaint is that they should have added a “1st” time version or selection where they took an extra minute to explain everything how to do, alternatives etc..  Otherwise I find myself having to look up to see and that often disrupts the exercise.  This might just be a problem because my TV is mounted up high though.

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Nix is Whispering

Here’s another sample of my writing.  Similar disclaimer, this was written while trying to go through the exercises from 3AM Epiphany and while trying to develop an evil character.  This is a work of fiction, this character is not nice.

3AM Epiphany – Challenge 2 – Write a fragment of a story that is made up entirely of imperative commands, e.g. “Do this; do that; contemplate the rear end of the woman who is walking out of your life.” This exercise will be a sort of second-person narration.

Wordcount: 500 (+/- 10%)

You’re getting very sleepy.  Very tired, just lay down on the bed now and rest your head.  That’s right just close your eyes now.  Shh baby don’t fret, don’t stir.  Sleep little one, rest your eyes and drink deeply of your dreams.  That’s right, perfect sleep soundly.  Now listen, but remain asleep little one.

There’s nothing to worry about.  Let your fears fall beside you.  There’s no need for your guard to be up, you’re safely asleep in your bed what could hurt you here.  Just relax and sleep deeply my darling one.  That’s a good boy.

You must sleep, you must rest, you have a big game coming up tomorrow.  It’s the championship game for you and your team, you’ve worked hard for it and must be ready.

But are you really ready?  Do you think you’re really strong enough and quick enough for this game?  Think of all the times you’ve thrown the ball only to see it intercepted by the other team.  Quite a few times if you think about it, think about it now – so many interceptions.  Or maybe think about the times you have fumbled and the other team has gotten the ball, how many games you have been responsible for the team losing.  Quite a few, if you think about it.

Think about the other team.  They have been so dominant in their wins, and your team has been well, less so.  You barely made it to this game in fact.  Do you really think you can defeat them?  Think about whether your team is infact strong enough and good enough to win the game tomorrow.  Maybe they are, maybe they are not.  But are you strong enough to be the deciding factor?  You wouldn’t want to cause your team to lose the game would you?

How could you live with that, how would it feel to know that you were the reason that all your teammates were disappointed and forever known as losers?  You couldn’t live with that could you?  Try to think about it, try to imagine in your dream what it would be like.  There are so many of your teammates that have promising futures ahead of them – if they win this game.  Is that something you could deal with, is that something you could hold in your conscience?

Tell the coach you cannot play.  Tell the coach that your arm hurts or that you feel sick.  You can tell him anything but you can’t play you can’t be the reason your team fails.  Do not be the one who steals your teammate’s futures from them.  You don’t want to be that, the source of their future struggles and failures.  You can’t play.  There is no way you can win if you play.  Tell the coach that, tell the coach to pull you from the game.  You’re not ready.

Now Wake Up!  Wake up this moment.  Its important for you to awaken, wasn’t there something you were going to do?  Don’t you have someone you must call?  Tell that person what you believe, tell them what you now understand.

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Adventures in Linux Ubuntu 10.10

I recently decided to get back into working with Linux.  My previous experience was running Redhat 6.2 and then 7.0 to support an Oracle 8/9 Server.   My first instinct was to install CentOS on my spare laptop – No VM for me! Well I did get CentOS 5x installed and configured with wireless it was an extreme fight.  I decided on a whim to dump the install and go with Ubuntu mainly because that’s what Rob Conery was using on his Tekpub videos.   I was astonished that installing ubuntu was a 1000x easier than was Centos.  I also loved the install process for the Server version and plan to work more with the Ubuntu Cloud offering soon.

The biggest and most exciting thing for me was that the ubuntu install instantly picked up the wireless card in my laptop.  This was huge as it took hours for me to get Centos to pick it up and had to go through many hoops and a lot more googling than I would have expected.  Now this isn’t hugely unexpected as CENTOS is meant to be an enterprise os and not a desktop operating system.  Mostly this was #ScottFail for not using the right tool for the job from the start.  That being said, I can’t state how awesomely pain free the process was.  I’m an ubuntu convert and for me that’s saying a lot.  I have a habit of sticking with one brand, what can I say? Marketing folks must love me.

 

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Exciting Technologies CUDA

One of the most exciting new technologies that I’ve worked with in the past year is definitely CUDA.  CUDA is a technology that allows for general purpose programming code – typically in c or c++ – to be compiled for and run on GPU devices.  What that means is the graphics card that’s in your high end laptop or desktop can now run general purpose code as well as the graphics code that its already running.

The potential for CUDA is amazing, it allows for massively parallel processing on the potentially hundreds of cores that are available on modern GPUs.  The laptop I’m writing this post on for instance has a NVIDIA 360M card which has 96 processing cores.  That’s compared to the 4 cores in the i7 chip that’s on the motherboard.  The cores are not truly general purpose, they can’t do everything that a modern CPU core can and they prefer to do work in one or more jobs that can be split across the cores.  Math and Physics simulations work extremely well.   While traditional CUDA is based in C there’s also a library called Thrust that allows for C++ programmers to get in the mix too.  Thrust provides very easy ways of transferring data from main memory to device memory as well as some awesome classes for things like map reduce.

There are a couple of uses that I would like to personally explore with CUDA.  Read only database querying.  I would love to be able to as a sample or research process create a dialect of SQL or a sub-set that allowed me to process simple traditional database queries on a CUDA capable device.  While there are a number of companies doing this sort of work, and probably this is something someone could buy instead of build, I think this would be a great chance to learn by doing.  Imagine if I had a table that was approximately 1GB in size with each row being about 128 bytes, that would be somewhere around 8M records in the table.   This works best if the individual records are numerical based, in otherwords large volumes of text aren’t a perfect fit.  In this case however, each of the 96 cores would have to process only ~90K records whereas the 4 cores of the cpu would have to process ~2M records.  While the table can be indexed in a traditional database system if the query patterns are known in advance, it certainly is exciting thinking about how a large volume of work can be spread against a number of cores  using CUDA.

Why use CUDA for something like this?  Why use it for filtering large sets of data?  Well let’s say that its a lot more than 1GB, let’s also say that the native format of the data is some form of binary structure.  To load 8M rows of data into a database it takes a non-trivial amount of time, and if the dataset is constantly being updated that’s a tax you’ll have to pay for every update.  Whereas a program written to leverage CUDA could likely query it directly and without that tax.   Also, this machine is just a laptop you could relatively inexpensively put together a machine with literally thousands of cores.  Imagine now that you had 2000 cores, with the same 8M rows, that’s only ~4K rows per core to filter.  Now that could be much faster.

This is a technology that I’m interested in and learning more about.  I’m sure that I’ve covered no new ground with this post and experts will probably be bored.  But perhaps there’s someone out there that wasn’t aware of CUDA or is just getting into it?  How are you finding it?  What have you found works, what doesn’t?

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