parallel-processing interview questions
Top parallel-processing frequently asked interview questions
Erg, I'm trying to find these two methods in the BCL using Reflector, but can't locate them. What's the difference between these two snippets?
A:
IEnumerable<string> items = ...
Parallel.ForEach(items, item => {
...
});
B:
IEnumerable<string> items = ...
foreach (var item in items.AsParallel())
{
...
}
Are there different consequences of using one over the other? (Assume that whatever I'm doing in the bracketed bodies of both examples is thread safe.)
Source: (StackOverflow)
I've been experimenting with multi threading and parallel processing and I needed a counter to do some basic counting and statistic analysis of the speed of the processing. To avoid problems with concurrent use of my class I've used a lock statement on a private variable in my class:
private object mutex = new object();
public void Count(int amount)
{
lock(mutex)
{
done += amount;
}
}
But I was wondering... how expensive is locking a variable? What are the negative effects on performance?
Source: (StackOverflow)
I have a question: what is the difference between concurrent programming and parallel programing? I asked google but didn't find anything that helped me to understand that difference. Could you give me an example for both?
For now I found this explanation: http://www.linux-mag.com/id/7411 - but "concurrency is a property of the program" vs "parallel execution is a property of the machine" isn't enough for me - still I can't say what is what.
Source: (StackOverflow)
I know C# is getting a lot of parallel programming support, but AFAIK there is still no constructs for side-effects verification, right?
I assume it's more tricky now that C# is already laid out. But are there plans to get this in? Or is F# the only .NET language that has constructs for side-effects verification?
Source: (StackOverflow)
Two new keywords added to the C# 5.0 language are async and await, both of which work hand in hand to run a C# method asynchronously without blocking the calling thread.
My question is, do these methods actually take advantage of multiple cores and run in parallel or does the async method run in the same thread core as the caller?
Source: (StackOverflow)
Many platforms promote asynchrony and parallelism as means for improving responsiveness. I understand the difference generally, but often find it difficult to articulate in my own mind, as well as for others.
I am a workaday programmer and use async & callbacks fairly often. Parallelism feels exotic.
But I feel like they are easily conflated, especially at the language design level. Would love a clear description of how they relate (or don't), and the classes of programs where each is best applied.
Source: (StackOverflow)
What's the status of multicore programming in Haskell? What projects, tools, and libraries are available now? What experience reports have there been?
Source: (StackOverflow)
I am porting some code to Parallel.ForEach and got an error with a continue I have in the code. Is there something equivalent I can use in a Parallel.ForEach functionally equivalent to continue in a foreach loop?
Parallel.ForEach(items, parallelOptions, item =>
{
if (!isTrue)
continue;
});
Source: (StackOverflow)
I was thrilled to see the new System.Collections.Concurrent namespace in .Net 4.0, quite nice! I've seen ConcurrentDictionary, ConcurrentQueue, ConcurrentStack, ConcurrentBag and BlockingCollection.
One thing that seems to be mysteriously missing is a ConcurrentList<T>. Do I have to write that myself (or get it off the web :) )?
Am I missing something obvious here?
Source: (StackOverflow)
I am trying to parallelize a ray-tracer. This means I have a very long list of small computations. The vanilla program runs on a specific scene in 67.98 seconds and 13 MB of total memory use and 99.2% productivity.
In my first attempt I used the parallel strategy parBuffer with a buffer size of 50. I chose parBuffer because it walks through the list only as fast as sparks are consumed, and does not force the spine of the list like parList, which would use a lot of memory since the list is very long. With -N2, it ran in a time of 100.46 seconds and 14 MB of total memory use and 97.8% productivity. The spark information is: SPARKS: 480000 (476469 converted, 0 overflowed, 0 dud, 161 GC'd, 3370 fizzled)
The large proportion of fizzled sparks indicates that the granularity of sparks was too small, so next I tried using the strategy parListChunk, which splits the list into chunks and creates a spark for each chunk. I got the best results with a chunk size of 0.25 * imageWidth. The program ran in 93.43 seconds and 236 MB of total memory use and 97.3% productivity. The spark information is: SPARKS: 2400 (2400 converted, 0 overflowed, 0 dud, 0 GC'd, 0 fizzled). I believe the much greater memory use is because parListChunk forces the spine of the list.
Then I tried to write my own strategy that lazily divided the list into chunks and then passed the chunks to parBuffer and concatenated the results.
concat $ withStrategy (parBuffer 40 rdeepseq) (chunksOf 100 (map colorPixel pixels))
This ran in 95.99 seconds and 22MB of total memory use and 98.8% productivity. This was succesful in the sense that all the sparks are being converted and the memory usage is much lower, however the speed is not improved. Here is an image of part of the eventlog profile.
As you can see the threads are being stopped due to heap overflows. I tried adding +RTS -M1G which increases the default heap size all the way up to 1Gb. The results did not change. I read that Haskell main thread will use memory from the heap if its stack overflows, so I also tried increasing the default stack size too with +RTS -M1G -K1G but this also had no impact.
Is there anything else I can try? I can post more detailed profiling info for memory usage or eventlog if needed, I did not include it all because it is a lot of information and I did not think all of it was necessary to include.
EDIT: I was reading about the Haskell RTS multicore support, and it talks about there being a HEC (Haskell Execution Context) for each core. Each HEC contains, among other things, an Allocation Area (which is a part of a single shared heap). Whenever any HEC's Allocation Area is exhausted, a garbage collection must be performed. The appears to be a RTS option to control it, -A. I tried -A32M but saw no difference.
EDIT2:
Here is a link to a github repo dedicated to this question. I have included the profiling results in the profiling folder.
EDIT3: Here is the relevant bit of code:
render :: [([(Float,Float)],[(Float,Float)])] -> World -> [Color]
render grids world = cs where
ps = [ (i,j) | j <- reverse [0..wImgHt world - 1] , i <- [0..wImgWd world - 1] ]
cs = map (colorPixel world) (zip ps grids)
--cs = withStrategy (parListChunk (round (wImgWd world)) rdeepseq) (map (colorPixel world) (zip ps grids))
--cs = withStrategy (parBuffer 16 rdeepseq) (map (colorPixel world) (zip ps grids))
--cs = concat $ withStrategy (parBuffer 40 rdeepseq) (chunksOf 100 (map (colorPixel world) (zip ps grids)))
The grids are random floats that are precomputed and used by colorPixel.The type of colorPixel is:
colorPixel :: World -> ((Float,Float),([(Float,Float)],[(Float,Float)])) -> Color
Source: (StackOverflow)
Possible Duplicates:
Iterate a list as tuples in python
How do I iterate over the tuples of the items of two or more lists in Python?
I have two iterables in Python, and I want to go over them in pairs:
foo = (1,2,3)
bar = (4,5,6)
for (f,b) in some_iterator(foo, bar):
print "f: ", f ,"; b: ", b
It should result in:
f: 1; b: 4
f: 2; b: 5
f: 3; b: 6
One way to do it is to iterate over the indeces:
for i in xrange(len(foo)):
print "f: ",foo[i] ,"; b: ", b[i]
But that seems somewhat unpythonic to me. Is there a better way to do it?
Source: (StackOverflow)
I need to execute some amount of tasks 4 at a time, something like this:
ExecutorService taskExecutor = Executors.newFixedThreadPool(4);
while(...) {
taskExecutor.execute(new MyTask());
}
//...wait for completion somehow
How can I get notified once all of them are complete? For now I can't think about anything better than setting some global task counter and decrease it at the end of every task, then monitor in infinite loop this counter to become 0; or get a list of Futures and in infinite loop monitor isDone for all of them. What are better solutions not involving infinite loops?
Thanks.
Source: (StackOverflow)
If
var arrayStrings = new string[1000];
Parallel.ForEach<string>(arrayStrings, someString =>
{
DoSomething(someString);
});
All 1000 Threads will spawn almost simultaneously?
Source: (StackOverflow)