Speakers of the Open Source, Multicore and Parallel Computing miniconf -

Wellington, NZ 19 January 2010

Schedule and Information about the miniconf

10:30 Ian Foster – Grid meets Cloud: Using Hosted Federation Services to Enhance Collaboration

Grid technologies have transformed the practice of science by facilitating resource sharing and collaborative work within distributed virtual organizations (VOs). However, the complexities inherent in deploying and operating grid tools remain a significant obstacle to wider use. The emergence of commercial infrastructure on demand (aka cloud) providers offers a potential solution to this problem. By offering VO support tools as hosted services rather than downloadable software, we can come closer to making the sharing of scientific data and methods as easy as the sharing of music videos.

In this talk, I present the motivations, early results, and future ambitions of a project, Globus.Org, that is exploring these ideas. The Globus Alliance is an active member in the community of Grid Software developers. As partners in e-Science and e-Business projects, we’ve built Grid Solutions for a variety of challenges that come up when people share resources. The Globus Alliance conducts research and development to develop the technology, standards, and systems that form the Grid: a computing architecture that enables distributed collaboration for business, science, engineering, and other human enterprises. Globus Alliance produces open-source software that is central to science and engineering activities totalling nearly a half-billion dollars internationally and is the substrate for significant Grid products offered by leading IT companies.

Bio – Ian Foster develops tools and techniques that allow people to use high-performance computers in innovative ways. He is the Associate Division Director for Mathematics and Computer Science at Argonne National Laboratory (ANL) and oversees the Distributed Systems Laboratory (DSL), which operates at both the University of Chicago and at ANL. The DSL serves as the nexus of the multi-institutional Globus Project.

Foster is director of the Computation Institute, a joint project between the University and ANL that addresses the most challenging computational and communications problems arising from a broad range of intellectual pursuits. Foster’s honors include the Lovelace Medal of the British Computer Society and the Gordon Bell Prize for high-performance supercomputing.

11:20 James Reinders – Threading Building Blocks (TBB), open sourcing a model for parallel computing

Abstract: TBB is a very popular abstraction for parallelism in C++. The project was introduced in 2006, and then open sourced by Intel in 2007. The talk is an overview of both the project, its popularity and adoption, and why open sourcing was critical to its success and how Intel settled on open sourcing. James will speak to the important role open source should have for parallel computing. James will also present his three tier model for parallelism (TBB is one of them) showing how data, task and coordination should co-exist in an parallel application – and suggest what is needed to fill in the other two models.

Bio – James Reinders is Director and Chief Evangelist, Intel Software Development Products. He was the primary driver in leading Intel to open source TBB. James is an expert in the area of parallelism, Intel’s leading spokesperson on tools for parallelism and the author of the O’Reilly Nutshell book on TBB. James has decades of experience with high degrees of parallelism having worked on groundbreaking compilers and architectures such as the systolic arrays WARP and iWarp, and the world’s first TeraFLOP supercomputer (ASCI Red)

13:30 Zhiyi Huang – View-Oriented Parallel Programming (VOPP)

Abstract: View-Oriented Parallel Programming (VOPP) is a novel parallel programming model that uses views for communication between multiple processes. A view is a group of data objects in shared memory. VOPP requires that all shared data are partitioned into non-overlapping views. With the introduction of views, mutual exclusion and shared data access are bundled together in VOPP, which offers both convenience and high performance to parallel programming. Furthermore, VOPP can relieve the issues such as data race and deadlock in parallel programming. This talk will address the issues of VOPP such as programmability, performance advantages, portability, and limitation. It will also compare with other popular programming models such as MPI, OpenMP, and Transactional Memory. Finally, performance results of VOPP will be demonstrated through two example VOPP environments: VODCA and Maotai, which are implemented for cluster computers and multi-core computers, respectively.

Bio: Dr. Zhiyi Huang is a Senior Lecturer in the Department of Computer Science at the University of Otago, New Zealand. He received his BSc degree in 1986 and PhD degree in 1992 in Computer Science from the National University of Defense Technology (NUDT) in China. From 1992 to 1996, he worked as a Chief Technical Officer (CTO) in industry while also lecturing in the Department of Computer Science at the Beijing Institute of Technology (BIT). Then he worked at the School of Computing & Information Technology at the Griffith University in Australia as a Research Fellow from 1996 to 1998. Since 1998, he has been lecturing at the University of Otago. Dr Huang had been a visiting professor at EPFL (Swiss Federal Institute of Technology Lausanne) and Tsinghua University in 2005, and a visiting scientist at MIT. He is now the Technical Liaison of the Sun Microsystems Center of Excellence in OpenSPARC that is based in the University of Otago.

13:55 Matthias Meyer – Scientific high-performance computing — educational bottlenecks in academia

Abstract: Multi-core is coming of age since it is our only work-around for the current technological boundaries in chip design. It constitutes a shift in paradigm, no doubt associated with a steep learning curve. What impact does this development have in the scientific community? At first sight — none. On the one hand, parallel computation is nothing new to those few who explore the edge of computability using special high-performance machines. On the other hand, the programming skills of the average researcher in the natural sciences are surprisingly often limited to Excel & Co. This knowledge gap between `computer-able’ scientists and those who use it as a typewriter is large, and it has profound consequences. The advent of general-purpose parallel computing here yields huge opportunities for science and FOSS therein. In this talk I will show examples of scientific high-performance computations, and I will highlight a few software projects which aim at providing a bridge between usability and high-performance. This talk is shaped by my personal experience and will therefore include an assessment of the current state of affairs of scientific computing in NZ.

Bio: Matthias Meyer is a recent physics PhD graduate in the MacDiarmid Institute for Advanced Materials and Nanotechnology at Victoria University of Wellington, New Zealand. His work and interests in scientific computing (and the role of open-source therein), is directly related with (massive-) parallel computations.

14:10 Timo Hoenig – Extending the Scope of Mobile Devices Running GNU/Linux

While servers and desktop computers have enough resources to fulfill challenging tasks, small devices such as mobile phones, mobile Internet devices (MID), netbooks and laptops are often limited in their use due to the resources they have. As systems in the near environment of such devices often can provide more resources it would be desirable to share those. The talk will discuss ongoing research efforts for a solution of this problem and consist of an theoretic part (describing the challenges and design considerations) and a practical part (showing the utilized subsystems and interfaces). Using existing technologies such as ZeroConf, Bonjour and Avahi it is possible for devices to discover available resources autonomously. A target system is able to accept and release virtual CPUs at run-time in order to access resources of an underutilized system when available. The allocation and deallocation of resources is transparent for applications as the underlying technologies are being handled in kernel space.

Bio: Timo Hoenig is member of the research staff at the Department of Computer Science 4 (Distributed Systems and Operating Systems Group) at the University of Erlangen-Nürnberg (Germany) and Senior Software Engineer at Novell, Inc. / SUSE Linux Products GmbH. Timo had been working exclusively on open source over the last six years

14:30 Stephen Blackheath – Haskell and Multi-core

Abstract: Haskell is an advanced general-purpose functional programming language, and entirely open source. It offers some new approaches to programming for multi-core processors. This presentation will cover Haskell’s current state of the art, as well as the up-coming “Data Parallel Haskell” system, and research into GPU programming. It aims to make the community aware of what Haskell has achieved and what it promises in the future for parallel/multi-core programming.

Bio: Stephen Blackheath lives in Manawatu, New Zealand, but spent most of his life in Wellington. Stephen worked as a software developer on many large commercial projects, and contributed to several open source projects. Major technology areas are embedded systems, internet infrastructure, several web applications, and telematics. In 2007 he started a new project and decided to do some research into new technologies, including an attempt to find out what was the ‘best language’. Out of that process discovered Haskell and functional programming. Currently works for an American start-up writing a video game in Haskell for the iPhone.

14:45 Paul Bone – Automatic Parallelism in Mercury

Abstract: Most future performance improvements will come from the addition of extra processor cores. Harnessing this increase in computing power is difficult. When using traditional synchronisation methods it is easy to introduce bugs or cause poor performance. It is difficult to decide what should be parallelised, this involves understanding the runtime behavior of the program and the overheads of parallel evaluation. We present a method for automatically parallelising programs written in purely declarative languages. We argue that automatic profile directed parallelisation is feasible and reduces the time and cost of software development. NB: We recommend to attend the previous presentation about Haskell and Multi-core as it provides background information.

Bio: Paul Bone is a computer science research student at the University of Melbourne who completed his Honours project in 2008 in automatic parallelisation of programs written in purely declarative programming languages. Prior to this, Paul worked in industry, including a number of commercial open source projects. Paul also contributes to Mercury, a purely declarative logic language.

15:00 – Rob Giltrap – Hunting for the World’s Largest Known Prime Numbers

Abstract: The Great Internet Mersenne Prime Search project has successfully found 13 new Mersenne Prime numbers and currently holds the top nine positions for the world’s largest known prime numbers. On any given day there are 60,000+ computers using spare computing cycles totaling over 43 TFLOP/s hunting for the next Mersenne prime number. Finds are rare (one every 1-2 years) and when one is discovered there is a race to rapidly verify the candidate, a process that typically takes over a week to complete. The Mlucas application (written primarily by Ernst W Mayer) is code developed for the fast verification of large prime numbers, driven by a high performance parallelised Fast Fourier Transform engine using OpenMP. In 2008, Mlucas was used to first verify what is currently the world’s largest known prime (a Mersenne prime at over 12.9 million digits in length) using 16 * SPARC64 VII CPU cores taking 13 days. This lightning talk will discuss the challenges of testing and tuning of the Mlucas application and system to deliver maximum performance at high core counts and then consider future challenges of utilising ever increasing core counts.

Bio: Rob Giltrap is a Solutions Architect for Sun Microsystems in New Zealand, focusing on high availability, high performance, mission critical system and storage solutions. A twenty year industry veteran he has a wealth of experience in squeezing the last ounce of performance out of systems and has verified the three largest known prime numbers in the last two years using large Sun systems. Rob has also been involved in many aspects of the open source community including running the local WellyLUG in it’s early years and was a founding member of the NZOSS Wellington branch.

15:45 Lenz Gschwendtner – Erlang, MPI, and open standards

Abstract: This talk is about message passing environments with a focus on message queues and AMQP as an open standard using it and Erlang.

Bio: Lenz Gschwendtner is a true geek. Currently is CTO of idegeeo Group Ltd and Open Source Evangelist at Core Technology Ltd. Previously, he was CTO of united-domains and responsible for domains at Lycos Europe. Lenz likes Perl, Erlang and life in New Zealand.

16:05 – Remo Williams – Titanic, Mars and Open New Zealand

Abstract: This talk is about the use of open source in the parallel computing environments with which I have had the pleasure of working (specifically, for a NASA Mars mission ground data processing at the University of Arizona’s Lunar and Planetary Laboratory, as well as for Digital Domain’s special effects for Hollywood). I will add some future-thinking thoughts on NZ as a country where to develop an open source philosophy and put my particular experiences into context to share how important I believe Open Source Parallel Computing is.

Bio: Remo Williams is a California surfer and an Arizona skateboarder with a passion for high-performance computing and open-source software. His MSc. is in Electrical and Computer Engineering focused on distributed object computing for modeling and simulation, and lead him to the world of Hollywood special effects. At Venice Beach-based Digital Domain, he wrote code for what may have been the world’s largest render farm at the time, a distributed Linux cluster of 105 DEC Alphas created to render the computer graphics for “Titanic”. This eventually lead Remo to implement an open-source Beowulf cluster of 32 Fedora nodes for NASA’s 2001 Mars Odyssey spacecraft mission, at the University of Arizona’s Lunar and Planetary Laboratory. Using MPI to coordinate Monte-Carlo based simulation code to help scientists “reverse engineer” the chemical composition of Mars’ surface and atmosphere through data from Odyssey’s Gamma Ray Spectrometer, these modeling and simulation results helped gain a better understanding of our neighbouring planet, as well as guide landing locations for subsequent NASA missions to Mars. Having himself landed in Gisborne, New Zealand, where he continues to teach skateboarding, Remo joined the open-source development team for eXe, a content authoring tool for educators that earned the 2008 IMS Global Learning Impact finalist and People’s Choice Award. Remo is now a computing lecturer at Gisborne’s Tairawhiti Polytechnic, where he is an open-source evangelist at any opportunity, and guides students into open-source and parallel computing projects wherever possible.

16:55 James Reinders – Teaching Parallel Programming

Abstract: Intel has been helping universities put together parallel programming classes in its program to bring material and professors together. In mid 2009, a few of the people behind this also taught a 3 day intensive class at Brooklyn Technical High School to high school students and teachers. They used open source projects in their teaching, giving the student opportunities to continue afterwards on their own systems easily. The speaker, James Reinders, has been highly involved in the university programs and will talk about the status of the program and the directions he’d like to see in further teaching of parallelism.

Part of LCA2010, the miniconf “Open Source, Multicore and Parallel Computing” will be a full day event in Wellington, New Zealand, the 19th of January 2010

The confirmed Schedule is

SCHEDULE

10:30 – 11:15 Ian Foster – Grid meets Cloud

11:20 – 12:15 James Reinders – TBB – Open sourcing a model for parallel computing

LUNCH

13:30 – 13:55 Zhiyi Huang -View-Oriented Parallel Programming

13:55 – 14:10 Matthias Meyer – Scientific high-performance computing

14:10 – 14:30 Timo Hoenig – Extending the Scope of Mobile Devices Running GNU/Linux

14:30 – 15:00 Parallelism in Declarative Languages

14:30 – 14:45 Stephen Blackheath – Haskell and Multi-core

14:45 – 15:00 Paul Bone – Automatic Parallelism in Mercury

15:00 – 15:15 Rob Giltrap – Hunting for the World’s Largest Known Prime Numbers

Interval

15:45 – 16:05 – Lenz Gschwendtner – Erlang, MPI, and open standards

16:05 – 16:30 – Remo Williams – Titanic, Mars and Open New Zealand

16:30 – 16:55 – James Reinders – Teaching Parallel Programming

16:55 – 17:15 – Panel –Who needs Parallelism? Moderator Nicolás Erdödy

17:15 – 17:30 – Birds of a Feather – Open Source, Multi-core and Parallelism: “the” software?

Abstracts and Bios of Speakers

Hello readers,

So I am here in L.A. for Microsoft’s biggest geek fest of the year – PDC 2009!! Unfortunately for me I will only be attending the pre-conference workshop session (you know, because there is like an economic recession of some sort going on these days). At any rate, I will be in Patterns of Parallel Programming workshop which will feature amongst others, the great Herb Sutter (of all things C++ fame) and Stephen Toub (Senior PM for parallel computing at MS). Here is a video precursor of the class –>
So I will start this blog off with some posts over the next few weeks covering topics of concurrency and parallel programming patterns based on the content discovered in this workshop. Stay tuned people!

Now a days, many of us know what parallel computing is. As the CPU clock cycle was increasing day by day, the problem of increasing power consumption was also arousing. The solution was to reduce the CPU clock cycle and multiple cores in to increase the processing power. Many computers now are multi core or many core systems. Dual Core and Quad core systems are the examples. Systems with more than previously mentioned cores are expected to come in near future as the demand of processing power is increasing.

We do have multi core systems but most of the programs that we use are not capable of utilize and exploit the power of multi core systems. Most of these software are based up on serialization. To exploit the power of multi core systems, software developers can parallelize their code to distribute work across multiple processors. Microsoft, which has always simplified programming for the developers, has also stepped up into parallel programming to make the programs utilize the power of multi core systems. In the new Microsoft Visual Studio 2010 and .NET Framework 4 Beta 2, there are some new features related to parallel programming:

• support for parallel programming with a new runtime
• new class library types, and diagnostic tools.

These features provides a friendly and easy way to develop efficient and scalable parallel applications without getting into low level programming and directly work with threads or the thread pool. The image below, provides a high level overview of the parallel programming architecture in .NET Framework 4 Beta 2:

The supports which is provided in Microsoft Visual Studio 2010 and .NET framework 4 Beta 2 for parallel programming can be categorized into these four areas

Task Parallel Library Overview:

The Task Parallel Library (TPL) is a set of public types and APIs in the System.Threading and System.Threading.Tasks namespaces in the .NET Framework version 4. These types rely on a task scheduler that is integrated with the .NET ThreadPool. The purpose of the TPL is to make developers more productive by simplifying the process of adding parallelism and concurrency to applications.It includes parallel implementations of for and foreach loops. It enables the developer to define concurrent, asynchronous tasks without having to work with threads, locks, or the thread pool.

Parallel LINQ (PLINQ):

PLINQ is a parallel implementation of LINQ to Objects that improvises the performance in many scenarios. PLINQ implements the full set of LINQ standard query operators as extension methods for the T:System.Linq namespace and has additional operators for parallel operations. PLINQ combines the simplicity and readability of LINQ syntax with the power of parallel programming

Data Structures for Parallel Programming:

The .NET Framework version 4 introduces several new types that are useful in parallel programming, including a set of concurrent collection classes, lightweight synchronization primitives, and types for lazy initialization. You can use these types with any multithreaded application code, including the Task Parallel Library and PLINQ.

Parallel Diagnostic Tools:

Includes debugger windows for tasks and parallel stacks, and concurrency views in the Visual Studio Team System Profiler that you can use to debug and to tune the performance of parallel code.

Sources: MSDN

The SC’09 will be next week in Portland, Oregon, USA.

“SC09 has adopted the theme of “Computing for a Changing World,” and will present world renowned speakers on initiatives related to Sustainability, Bio-Computing and the 3D Internet.”

“Over the next 5 years we expect the extended SC community to play an important role in leading the mainstream of computing into an era of parallelism. “

Some of the abstracts of the keynotes at SC’09 are particularly interesting

The Rise of the 3D Internet – Intel CTO, Justin Rattner

“Forty Exabytes of unique data will be generated worldwide in 2009. This data can help us understand scientific and engineering phenomenon as well as operational trends in business and finance. The best way to understand, navigate and communicate these phenomena is through visualization. In his opening address, Intel CTO Justin Rattner will talk about today’s data deluge and how high performance computing is being used to deliver cutting edge, 3D collaborative visualizations. He will also discuss how the 2D Internet started and draw parallels to the rise of the 3D Internet today. With the help of demonstrations, he will show how rich visualization of scientific data is being used for discovery, collaboration and education.”

A couple of other presentations caught my attention (apart from Al Gore and his view on climate change

HPC and the Challenge of Achieving a Twenty-Fold Increase in Wind Energy

The Outlook for Energy: Enabled with Supercomputing

“The presentation reviews ExxonMobil’s global energy outlook through 2030. The projections indicate that, at that time, the world’s population will be ~8 billion, roughly 25% higher than today. Along with this population rise will be continuing economic growth. This combination of population and economic growth will increase energy demand by over 50% versus 2000. As demand rises, the pace of technology improvement is likely to accelerate, reflecting the development and deployment of new technologies for obtaining energy–to include finding and producing oil and natural gas. Effective technology solutions to the energy challenges before us will naturally rely on modeling complicated processes and that in turn will lead to a strong need for super computing. Two examples of the supercomputing need in the oil business, seismic approaches for finding petroleum and petroleum reservoir fluid-flow modeling (also known as “reservoir simulation”) will be discussed in the presentation.”

An interesting way to put all these ideas in a less “marketing driven” context is to read the interview with Rick Stevens from Argonne, about “reaching the next milestone in computing history: the exaflops computer.”

I tried to summarise the article, but actually it’s simply better that you go through it and have a glimpse of the future of Supercomputing, which soon (10 years?) won’t be supercomputing but just computing.

So, what’s exaflops?

FLOPS = In computing, FLOPS (or flops or flop/s) is an acronym meaning FLoating point Operations Per Second. The FLOPS is a measure of a computer’s performance, especially in fields of scientific calculations that make heavy use of floating point calculations, similar to the older, simpler, instructions per second. (Wikipedia)

exaFLOPS = 10^18 = 1, 000, 000, 000, 000, 000, 000 operations per second.

That’s why Rattner is so excited about 3D internet and other applications.  In this very good interview, he starts by saying that 3D internet is where HPC “goes consumer.”

The article from HPC wire has a good history of HPC and different players, and finishes quoting Rattner saying:  “If the 3D, immersive experience becomes the dominant metaphor for how people experience the internet of tomorrow, we won’t have to worry about who will build the processors and computers that do HPC. Everyone will want to be a part of that.”

Are you planning to be “part of that”?

Nicolás Erdödy

North Otago, New Zealand

After the Nvidia GPU conference I’ve been reading up on the Fermi architecture. Now for gaming, the card is cool, but you quickly realize that gaming is not its targeted audience. It just happens to be that the work I do has a lot to do with images and doing stuff in parallel. The thing with images are that they can usually be very of very high resolution and the output might consist of voxels which also might be of high resolution. So far bandwidth has been a big bottleneck. Even though the PCI-express is incredibly fast, the calculations might actually be faster than the transfer. Therefore if one applies SIMD instructions and take advantage of the considerably larger memories on 64-bit machines thinks are done faster since you don’t need to shuffle stuff around.

This has been, in my own humble opinion, a big issue for the professional market. Of course at the GPU conference many companies shared their thoughts on the subject and showed that although this is a limitation, it is possible to work around. The bad news of course is that it requires one to have good knowledge of how CUDA utilies the raw power of graphics card. Such knowledge takes around a year or two and hasn’t been much of an option for companies without proper R&D.

Thankfully Nvidia acknowledges the issue and therefore they implemented 64-bit memory addressing capabilities on the Fermi card (actually the first gen is going to use like 40 bits) which in turn allows for those 8 GB graphics card. For the professional market this is the right way to go, and programmers will always be happy with more memory (if a bit more lazy).

The next thing that blew me out of the water is the raw computation power of the Fermi architecture. Now, for single precision calculations graphic cards have been viable for quite some time. But when doing stuff in a more scientific way you always want double precision. The Cell processor has so far been a real killer at this, and if the memory wasn’t so lousy on the Playstation 3 could possibly become the weapon of choice (4 SIMD registers per SPU if I recall correctly, proved 10 times faster number crunching than Intel processor). Now the Fermi has 512 cores, which I think would translate into registers? Anyway, with 16 Streaming Multiprocessors each with 32 single precision calculations per cycle the Fermi card shows incredible potential. Especially as doing double precision is not suppose to be slower (giving 16 calculations per cycle). Now this I won’t know before testing, if given the opportunity of course. Still the sum becomes 256 double precision calculations per cycle compared to 2 per core on a normal processor. Even with new quad cores with utilizing hyper threading and having 2-4 times the clock rate the Fermi should still outperform considerably.

I can only assume the Larrabee will blow Fermi out the water (because it has to), and there fore the parallel computing power on the horizon must be crazy. Exciting times for the performance geek. Also, Nexus allows for proper debugging of CUDA (FINALLY!) which will allow companies to capitalize on this sick performance more quickly.

Neuron ‘09, a technical fest, was held between 23rd and 24th of October, 2009 in my institute and I must say, those guys managed to pull it off pretty well! A once in a blue moon situation, most of the events violated the ‘Indian Standard Time’ rule by actually beginning and ending on time! When’s the last time you saw that happen here? Anyways, as always, we from the MNIT Open Source User Mesh (MOSUM) decided to conduct a little FOSS workshop during the three day programme. The 24th of October was the auspicious date as per the alignment of the planets (yeah right). So just like we did with all our other workshops that happened during our tech fests, we decided to bring in speakers from outside. Steven Fernandez (who works for Druvaa, and is also a former Red Hat employee) talked about the FOSS ecosystem, how it works and how one can be a part of it. Jai Pandya (JECRC, Jaipur) followed with a beginner oriented talk on WordPress and how to use it setup a website in under 5 minutes. Finally, I took over with a not-so-beginner-oriented talk on parallel programming using OpenMP (#pragma anyone?). Furthermore, the turnout of 120 was far more than any of us expected! Wonder if the city of Jaipur is really awakening. Let’s just hope that we see new faces turning up for our LUG-Jaipur meets from here on.

James Reinders,  Chief Software Evangelist and Director of Intel Software Development Products will be one of the keynotes at the Miniconference “Open Source, Multicore and Parallel Computing” in Wellington, 19 January 2010.

James is an expert in the area of parallelism, Intel’s leading spokesperson on tools for parallelism, and author of the O’Reilly Nutshell book on the C++ extensions for parallelism provided by the popular Intel Threading Building Blocks (TBB)

Will post shortly the abstract of his presentation (around TBB of course) but want to highlight a shared interest: teaching parallelism in high schools. More in this post

Shortly will be posting more information about James activities during his visit.

Nicolás Erdödy

Oamaru, New Zealand

Posted on http://www.ddj.com/go-parallel
The interest on Rich Services Cloud Applications is growing fast. Users want responsive and immersive interactions from any locations. Nowadays, you cannot think about a business application without mobility in mind. However, you cannot avoid creating a rich user experience (UX) in mobile devices whilst accessing services on the cloud. If you want to offer a really nice experience, you’ll have to use parallel programming skills everywhere.
Read more here

Posted on http://www.ddj.com/go-parallel
Process Monitor is a very complete advanced monitoring tool that shows and logs real-time activity for the file system, the Registry, the running processes and their threads in Windows. Yesterday, the Windows Sysinternals team made the new version v2.7 of Process Monitor available for download.
Read more here

Posted on http://www.ddj.com/go-parallel
Most modern Web pages run scripts. So far, there are many limitations to allow these scripts to take advantage of multicore microprocessors. However, Web Workers is a draft specification that defines an API to allow Web application authors to spawn background workers running scripts in parallel.
Read more here

Posted on http://www.ddj.com/go-parallel
The new Parallel Extensions offered by .NET Framework 4 Beta 1 present developers the opportunity to use the new parallel loops. Using them, it is easier to distribute tasks in many cores. However, you don’t have to forget about concurrency issues.
Read more here

I’ve been invited to “the exclusive Talk Parallel session” with James Reinders this Thursday, Sept. 24, at 8 a.m. PST. (brrrr!! it will be 3:00 am Friday 25 in New Zealand!!)

I already warned wife and kids that they don’t need to worry about me turning insomniac and talking parallelism in the middle of the night…It is just an example of the sacrifices of entrepreneurship…:-))

With 20 years at Intel, today James is the Chief Evangelist + Director of Marketing & Sales Development at Intel’s Software & Solutions Group, based in Portland, Oregon. But above all, looks like a cool guy from our email and LinkedIn exchanges.

“…the live chat will take place via the Internet, so no phone call-in will be needed. We hope this will be most convenient for the participants on the road at IDF.”

The invitation keeps saying: “So, what’s different about this session with James? Talk Parallel is an opportunity to submit your questions, plus gain insight from the dialogue with others who are also deeply involved in writing and thinking about parallelism. As a preview of the questions James will address, here’s a sampling of a few submitted by your peers:“

•	Do you have plans to add support for other programming languages in future Intel® Parallel Studio and Intel® Parallel Advisor versions? Are C#* and/or Java* in the future plans?
•	The Von Neumann bottleneck will ultimately limit the number of cores connected to an individual memory. I see a hybrid future of blended OpenMP* and MPI* algorithms. What future do you see, what predominant architectures, and what programming paradigms?
•	Is the penny starting to drop among developers who fail to see independent streams and take advantage of parallelism again and again?

I also submitted my questions

But will post later a balance of the conversation.

What caught my attention earlier this year about James’ activities was the workshop on teaching parallelism in a high school (see post). The best summary of this initiative is the sentence “…plant seeds in minds that can solve problems that don’t yet exist”. This article also gives a brief about the experience.

Then I started to think that if it is possible in high school, why not primary school.

Next week will meet with the Principal of the school of my 9 years old son…If Piaget studied his children to develop his theories, why not try with the (less?) ambitious goal of “thinking parallel” from scratch?

Nicolás Erdödy

Oamaru, New Zealand

Lately, I have been following extensively projects related to

DPH for Haskell
Clang/LLVM
Unladen Swallow
Apple GCD
OpenCL
CUDA

I think these topics would probably indicate that I am very interested in performance. In fact this is the case because everyday I am playing with different computation on hundreds of MB of data if not thousands. Waiting for few minutes are getting on my nerve.