Aater Suleman

Aater Suleman is a computer architect by profession He tackles the hardware and software challenges posed by multi-core architectures on a daily basis. Suleman received his BSEE, MSEE, and PhD in Computer Engineering from the University of Texas at Austin. His honors include the IEEE Micro Top Picks award, an annual award to recognize the ~10 most significant and influential papers published in top computer architecture conferences; Dr. Suleman has received this honor twice (in 2009 and 2010). Suleman was also awarded the Intel PhD fellowship and the Prestigious Graduate Dean Fellowship. A sensor system designed by Suleman is currently in-use by NASA's Ice, Cloud, and Elevation Satellite. Suleman continues to publish actively in top journals and conferences. More information regarding Dr. Suleman and his work can be found at http://hps.ece.utexas.edu/people/suleman . Disclaimer: The views are Aater's own views and do not reflect those of his employers.

Dec 132013
Hadoop Logo



At Flux7Labs we have done a detailed comparison of all too Hadoop distributions. We not only compared performance using Intel HiBench benchmarks but also compared more subjective metrics like ease of installation, usability, and ecosystem support. Head over to Flux7 blog to read the whitepaper. As always, feedback is highly appreciated.

Read – A Detailed Comparison of Hadoop Distributions now.


Jun 182013

I made a major career decision two months ago to leave my day job and start Flux7 labs, a consulting and training firm. I made this decision because Flux7 Labs allows me to follow my passion of teaching (providing Big Data/NoSQL trainings) and solving challenges in latest technologies like Hadoop, Cassandra, Twitter Storm, etc. Please visit the LinkedIn profile to learn more.

One of the best parts is that I will have more time and incentive to write blog posts. For those of you who read my post on Linked Lists, I am finally doing a performance benchmark to generate data that proves my points. For those interested in Big Data, I am writing a qualitative and quantitate comparison of different Hadoop distributions out there. Exciting times ahead.


Continue reading “Meet Flux7 Labs (update + shameless marketing)” »

Jul 162012

Raspberry Pi, Mele A1000, MK802, and … . the market is getting filled with these low price geek toys. I personally see a lot of potential here. These “devicelets” can do to hardware what apps did to software. Some readers may remember that I posted a tutorial to create a simple evaluation board out of a iPhone 3GS last year. Back then, Pandaboard was the only choice to get an ARM computer in the market and it was never available. Now there are so many vendors and sellers that it has become difficult to chose. This post is just a concise summary of all the available choices I have come across so far.

Continue reading “Which little PC should I buy? Raspberry Pi? Mele A1000? or …” »

Jul 132012

After I downloaded  iOS6 on my iPhone last week, the first icon I clicked on was Passbook only to find that Apple had not put any example passes in there. Since Passbook was the primary reason I had downloaded iOS6, I dug into the API and learned how to create a pass myself. It was a great learning experience that I want to share with others. I also provide a shell script to automate the pass generation process and also present to you, iPass.pk, a user-friendly GUI-based service to create passes.

Continue reading “Generating passes for iOS6′s Passbook” »

Jun 302012

Yet another hiatus. Sorry, I was very busy with my job as a performance architect at Calxeda. Will try to be regular again. 

I have recently been interviewing people at Calxeda, my new employer. There are a few fundamental concepts I expect every engineer/CS major to understand, regardless of what position they are applying for. One of them is the difference between a channel’s throughput and its latency. It is surprising how many candidates get it wrong. I will not only try to explain the concepts of latency and throughput using a simple analogy, but also try to hypothesize why IMO most people get them confused.

Continue reading “Clarifying Throughput vs. Latency” »

Aug 242011

I typically do not share articles on this blog but I found this white paper today which was very enlightening and doesn’t seem to have gotten the deserved attention. The author has done an excellent job of explaining the shortcomings of GNU Make. I now question why I use Make:-)


Below is excerpt and a link to the article. Since the original post doesn’t have space for comments, we can use this post for our discussion.


GNU make is a widely used tool for automating software builds. It is the de facto standard build tool on Unix. It is less popular among Windows developers, but even there it has spawned imitators such as Microsoft’snmake.

Despite its popularity, make is a deeply flawed tool. Its reliability is suspect; its performance is poor, especially for large projects; and its makefile language is arcane and lacks basic language features that we take for granted in other programming languages.

Admittedly, make is not the only automated build tool. Many other tools have been built to address make’s limitations. Some of these tools are clearly better than make, but make’s popularity endures. The goal of this document is, very simply, to educate you about some of the issues with make—to increase awareness of these problems.


Read more

Aug 092011

Similar to other prediction mechanisms, branch predictors are also better at predicting strongly biased branch outcomes.

This rule is well-understood and commonly used, e.g., the Intel Itanium compiler assumes that prediction accuracy = MAX(percentage_taken, percentage_not_taken) when performing its profile-guided optimizations. Thus, to improve branch prediction, we must increase the number of biased branches while reducing branches that are oscillating. This post shows a simple trick to do so.

Continue reading “Quick Post: Software Trick to Improve Branch Prediction” »

Aug 072011

Big-O gives us a tool to compare algorithms’ efficiency and execution times without having to write the code and do the experiments. However, I feel that many people misuse the analysis unknowingly. Don’t get me wrong. I am also a big fan of analytic models and understand that they provide insights that cannot be found empirically. However, in case of Big-O, I feel that it has underlying assumptions that were true when it was formed but have since become false. Thus, we need a revision of how Big-O should be taught. This post explains why…

Continue reading “Why Big-O needs an update” »

Aug 072011

The purpose of this post is two fold. First, I want to raise awareness about the transformations a problem goes through before it can be solved by the electrons running around  in the hardware. It is common knowledge for many of you but listing this can be useful for the younger readers. Second, I want to share Prezi, a web-based tool to make presentations. This is my first experience with Prezi and I liked the interface and options better than Powerpoint. I figured I will convey some useful information with the demo.

Continue reading “Quick Post: Levels of Transformation in Computer Programs (+Prezi)” »

Aug 052011
Source: http://smartincomeblog.com/what-i-learned-from-creating-an-iphone-app

In a weak moment last July, I paid $99 for an Apple Developer Account with the intent to learn iPhone app development. However, I didn’t use it for 11.5 months. When I learned two weeks ago that I was about to lose my investment, I decided to salvage it. It has actually been a great experience and I don’t regret spending the week playing with iPhone apps. I have not become an expert by any means but I think I have learned enough to have some opinions. I am writing this article to share what I learned as it may interest some other “traditional” computer scientists to explore iOS.

Continue reading “iPhone App Development (for Old School Coders)” »