The real problem exists in determining the critical section of your source code. Game Developer or Hobiest, you still have to deal with splitting up what parts you want to run where. As of now I don’t know of any smart scheduler that will handle that for you.

Recalling what I read of PS3 developers, they had to either run sections of sound, video, mesh parsers on individual cores or designate critical sections to some sort of scheduler.

Nobody really knows what will work best. It takes development time that nobody seems to have anymore. It’s all about release dates. But that is a story for another time.

I have a dual-core 32-bit intel laptop. My real problem with the industry is that my parents’ single core 32/64-bit amd desktop leaves it behind as one would a bad dream.

What happens is if you want real performance then you need real tools. Logic sims for the processor and assembler commands “reference code, docs, .
You really need to know the architecture you are working on. Registers if you will. Think about the Jaguar, Atari developers. They knew the processors and interleave times. Once you have all that information gathered you can start programming for your then out of date processor which is another problem with the industry.

I mean, in case of uniprocessor and multiprocessor environment.

As per as my knowledge is concerned, in uniprocessor , we should use mutex and in multiprocessor, we should use spin lock.??

Please explain is it right or wrong?

* garbage collection

C++ has 3rd party garbage collection, and in all flavors too. You can get a reference counting GC or use a Mark and Sweep one or whatever other algorithms are out there. They work pretty well and override the global operator “new” function. Check out Stroustrup’s FAQs for pointers on this part. http://www.research.att.com/~bs/bs_faq.html#garbage-collection

* array bounds checking

Just pointing out that you can use std::vector.at() and you’ll get bounds checking. I find it hard to think of situations when I’d use an array over a std::vector.

* built-in support for threads

A valid complaint, just noting that C++0x will hopefully rectify that situation (Stroustrup says “C++0x will almost certainly include a threads library.” in his FAQ).

* no fall-through on switch-statements
* arithmetic operations can be checked for overflow if required

These sound pretty awesome. I’ll have to look into C# just for these feature alone.

* objects must have a definite value before being used

I’m somewhat confused by what you mean about this. If you don’t provide a default constructor in C++, you are forced to initialize every object, or else you get a compile time error. Perhaps you mean primitives must have definite values?

My first question is who cares about that multicore crisis? Should I care? And if, why?
We are talking about a problem software developers have or maybe will have (oh yes, WE already had the crisis in 1999). All developers? Me? No. Not me. Why?

Let me go into greater detail to explain what I mean. As cpus became faster and faster new CASE tools became available that allowdevelopers using more and more abstract designs for application development. Those tools create code, integrate libraries and put general purpose code into your application. The effect is a shorter time to market paid with more calculation overhead.

An example: Create a hello world application in 1970, 1990 and 2008. They all will say “Hello world” but the first will run 5000 cpu cycles, the second 500,000 and the last more than 10,000,000 cycles. The hello world app of 2008 won’t be slower though. Why? Because the cpu it will run on is more than 10,000 times faster that that of 1970.

Now back to the crisis. My problem is that the application I just created dosn’t meet the performance requirements on the target architecture. A faster cpu isn’t available and it doesn’t scale in a multicore environment. You can call that a multicore crisis if you want. Why not call it an overhead crisis?

There is so called redshifting business, right. Google, Ebay and the military won’t solve their capacity problems by going back to assembler programming. But as smoothspan wrote in his blog in 2007 - they already have a solution! So they aren’t hit by the crisis right now and won’t be in the nearer future.

Maybe the mid-sized software companies are. Those that deliver 95% of the applications in use by 95% of the people. Those that deliver applications that don’t scale well in multicore environments. Those that use the tools that generate code that keeps a cpu busy with overhead most of the time. Runtime analysis of legacy software systems (that, in my opinion, make up more than 50% of all software systems) shows that a cpu spends most of its time in calculating things the programmer has no idea of. Listen to them, they will tell you something like “what the hell is …” or “which crazy bastard created that routine?”.

Back to my optimization problem. I don’t have the knowledge and skills to transform my algorithms in well scaling parallel ones. Maybe I get it running on two cpus, maybe on four. But N is unreachable. But if I had, I wouldn’t do it anyways. This is mainly a question of my application doing the right things rather than doing the (wrong) things right (in this case: faster).

As long as applications are as described there will be no multicore crisis. Today’s business applications don’t perform operations 10,000 times more complex than those of 1970. Because today’s cpus deliver 10,000 times more calculation power there is no need for more cpus. After that it is all about a cost problem. The question is: Is parallel programming cheaper than creating less redundant code?

1) $PATH=$PATH:/opt/intel/cc/9.1.044/bin (enter)
2) $export PATH (enter)
3) $LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/cc/9.1.044/lib (enter)
4) $export LD_LIBRARY_PATH (enter)

Thanks to all

A: Go Read myblog

Q: But what about . . .?

A: Go Read myblog

Tell us something useful here since this is the page we actually wanted to come to, not myblog

PATH=$PATH:/opt/intel/cc/9.1.044/bin/
export PATH

LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/cc/9.1.044/lib
export LD_LIBRARY_PATH

I just downloaded 10.1.008 from intels website and everything works perfectly on ubuntu gutsy 7.10

I have a pentium celeron 556 Mhz 384 mb ram computer with linux installed

Thanks again for the excellent tutorial…

nice blog. It would be interesting to see the more information about the parallel programming.

By the way to answer Josh’s question. I pusblished the paper at IWOMP in China about Transactional Memory and OpanMP. You can find it on my web page . We plan to publish the TM+OpenMP compiler and runtime soon. I hope in less than one month. So I’ll let you know.