Re: parallel threads stalls until all thread batches are finished.
On Monday, 28 August 2023 at 22:43:56 UTC, Ali Çehreli wrote: On 8/28/23 15:37, j...@bloow.edu wrote: > Basically everything is hard coded to use totalCPU's parallel() is a function that dispatches to a default TaskPool object, which uses totalCPUs. It's convenient but as you say, not all problems should use it. In such cases, you would create your own TaskPool object and call .parallel on it: https://youtu.be/dRORNQIB2wA?t=1611s Ali Thanks. Seems to work. Didn't realize it was that easy ;)
Re: parallel threads stalls until all thread batches are finished.
On 29.08.23 00:37, j...@bloow.edu wrote:
Well, I have 32 cores so that would spawn 64-1 threads with hyper
threading so not really a solution as it is too many simultaneous downs
IMO.
"These properties get and set the number of worker threads in the
TaskPool instance returned by taskPool. The default value is totalCPUs -
1. Calling the setter after the first call to taskPool does not changes
number of worker threads in the instance returned by taskPool. "
I guess I could try to see if I can change this but I don't know what
the "first call" is(and I'm using parallel to create it).
The call that is interesting in your case is the call to `taskPool` in
your foreach loop. So if you call `defaultPoolThreads(8)` before your
loop you should be good.
Seems that the code should simply be made more robust. Probably a just a
few lines of code to change/add at most. Maybe the constructor and
parallel should take an argument to set the "totalCPUs" which defaults
to getting the total number rather than it being hard coded.
I currently don't need or have 32+ downlaods to test ATM so...
this() @trusted
{
this(totalCPUs - 1);
}
/**
Allows for custom number of worker threads.
*/
this(size_t nWorkers) @trusted
{
Basically everything is hard coded to use totalCPU's and that is the
ultimate problem. Not all tasks should use all CPU' >
What happens when we get 128 cores? or even 32k at some poin >
It shouldn't be a hard coded value, it's really that simple and where
the problem originates because someone didn't think ahead.
You have the option to not use the default value.
Kind regards,
Christian
Re: parallel threads stalls until all thread batches are finished.
On 8/28/23 15:37, j...@bloow.edu wrote: > Basically everything is hard coded to use totalCPU's parallel() is a function that dispatches to a default TaskPool object, which uses totalCPUs. It's convenient but as you say, not all problems should use it. In such cases, you would create your own TaskPool object and call .parallel on it: https://youtu.be/dRORNQIB2wA?t=1611s Ali
Re: parallel threads stalls until all thread batches are finished.
On Monday, 28 August 2023 at 10:33:15 UTC, Christian Köstlin
wrote:
On 26.08.23 05:39, j...@bloow.edu wrote:
On Friday, 25 August 2023 at 21:31:37 UTC, Ali Çehreli wrote:
On 8/25/23 14:27, j...@bloow.edu wrote:
> "A work unit is a set of consecutive elements of range to be
processed
> by a worker thread between communication with any other
thread. The
> number of elements processed per work unit is controlled by
the
> workUnitSize parameter. "
>
> So the question is how to rebalance these work units?
Ok, your question brings me back from summer hibernation. :)
This is what I do:
- Sort the tasks in decreasing time order; the ones that will
take the most time should go first.
- Use a work unit size of 1.
The longest running task will start first. You can't get
better than that. When I print some progress reporting, I see
that most of the time N-1 tasks have finished and we are
waiting for that one longest running task.
Ali
"back to sleep"
I do not know the amount of time they will run. They are files
that are being downloaded and I neither know the file size nor
the download rate(in fact, the actual download happens
externally).
While I could use work unit of size 1 then problem then is I
would be downloading N files at once and that will cause other
problems if N is large(and sometimes it is).
There should be a "work unit size" and a "max simultaneous
workers". Then I could set the work unit size to 1 and say the
max simultaneous workers to 8 to get 8 simultaneous downloads
without stalling.
I think thats what is implemented atm ...
`taskPool` creates a `TaskPool` of size `defaultPoolThreads`
(defaulting to totalCPUs - 1). The work unit size is only there
to optimize for small workloads where task / thread switching
would be a big performance problem (I guess). So in your case a
work unit size of 1 should be good.
Did you try this already?
Kind regards,
Christian
Well, I have 32 cores so that would spawn 64-1 threads with hyper
threading so not really a solution as it is too many simultaneous
downs IMO.
"These properties get and set the number of worker threads in the
TaskPool instance returned by taskPool. The default value is
totalCPUs - 1. Calling the setter after the first call to
taskPool does not changes number of worker threads in the
instance returned by taskPool. "
I guess I could try to see if I can change this but I don't know
what the "first call" is(and I'm using parallel to create it).
Seems that the code should simply be made more robust. Probably a
just a few lines of code to change/add at most. Maybe the
constructor and parallel should take an argument to set the
"totalCPUs" which defaults to getting the total number rather
than it being hard coded.
I currently don't need or have 32+ downlaods to test ATM so...
this() @trusted
{
this(totalCPUs - 1);
}
/**
Allows for custom number of worker threads.
*/
this(size_t nWorkers) @trusted
{
Basically everything is hard coded to use totalCPU's and that is
the ultimate problem. Not all tasks should use all CPU's.
What happens when we get 128 cores? or even 32k at some point?
It shouldn't be a hard coded value, it's really that simple and
where the problem originates because someone didn't think ahead.
Re: parallel threads stalls until all thread batches are finished.
On 26.08.23 05:39, j...@bloow.edu wrote: On Friday, 25 August 2023 at 21:31:37 UTC, Ali Çehreli wrote: On 8/25/23 14:27, j...@bloow.edu wrote: > "A work unit is a set of consecutive elements of range to be processed > by a worker thread between communication with any other thread. The > number of elements processed per work unit is controlled by the > workUnitSize parameter. " > > So the question is how to rebalance these work units? Ok, your question brings me back from summer hibernation. :) This is what I do: - Sort the tasks in decreasing time order; the ones that will take the most time should go first. - Use a work unit size of 1. The longest running task will start first. You can't get better than that. When I print some progress reporting, I see that most of the time N-1 tasks have finished and we are waiting for that one longest running task. Ali "back to sleep" I do not know the amount of time they will run. They are files that are being downloaded and I neither know the file size nor the download rate(in fact, the actual download happens externally). While I could use work unit of size 1 then problem then is I would be downloading N files at once and that will cause other problems if N is large(and sometimes it is). There should be a "work unit size" and a "max simultaneous workers". Then I could set the work unit size to 1 and say the max simultaneous workers to 8 to get 8 simultaneous downloads without stalling. I think thats what is implemented atm ... `taskPool` creates a `TaskPool` of size `defaultPoolThreads` (defaulting to totalCPUs - 1). The work unit size is only there to optimize for small workloads where task / thread switching would be a big performance problem (I guess). So in your case a work unit size of 1 should be good. Did you try this already? Kind regards, Christian
Re: parallel threads stalls until all thread batches are finished.
On Friday, 25 August 2023 at 21:43:26 UTC, Adam D Ruppe wrote: On Wednesday, 23 August 2023 at 13:03:36 UTC, Joe wrote: to download files from the internet. Are they particularly big files? You might consider using one of the other libs that does it all in one thread. (i ask about size cuz mine ive never tested doing big files at once, i usually use it for smaller things, but i think it can do it) The reason why this causes me problems is that the downloaded files, which are cashed to a temporary file, stick around and do not free up space(think of it just as using memory) and this can cause some problems some of the time. this is why im a lil worried about my thing, like do they have to be temporary files or can it be memory that is recycled? The downloading is simply a wrapper that provides some caching to a ram drive and management of other things and doesn't have any clue how or what is being downloaded. It passes a link to something like youtube-dl or yt-dlp and has it do the downloaded. Everything works great except for the bottle neck when things are not balancing out. It's not a huge deal since it does work and, for the most part, gets everything downloaded but sorta defeats the purpose of having multiple downloads(which is much faster since each download seems to be throttled). Increasing the work unit size will make the problem worse while reducing it to 1 will flood the downloads(e.g., having 200 or even 2000 downloads at once). Ultimately this seems like a design flaw in ThreadPool which should auto rebalance the threads and not treat the number of threads as identical to the worker unit size(well, length/workerunitsize). e.g., suppose we have 1000 tasks and set worker unit size to 100. This gives 10 workers and 10 workers will be spawned(not sure if this is limited to total number of cpu threads or not) What would be nice is to be able to set worker unit size to 1 and this gives 1000 workers but limit concurent workers to, say 10. So we would have at any time 10 workers each working on 1 element. When one gets finished it can be repurposed for any unfinished tasks. The second case is preferable since there should be no issues with balancing but one still gets 10 workers. The stalling comes from the algorithm design and not anything innate in the problem or workload itself.
Re: parallel threads stalls until all thread batches are finished.
On Friday, 25 August 2023 at 21:31:37 UTC, Ali Çehreli wrote: On 8/25/23 14:27, j...@bloow.edu wrote: > "A work unit is a set of consecutive elements of range to be processed > by a worker thread between communication with any other thread. The > number of elements processed per work unit is controlled by the > workUnitSize parameter. " > > So the question is how to rebalance these work units? Ok, your question brings me back from summer hibernation. :) This is what I do: - Sort the tasks in decreasing time order; the ones that will take the most time should go first. - Use a work unit size of 1. The longest running task will start first. You can't get better than that. When I print some progress reporting, I see that most of the time N-1 tasks have finished and we are waiting for that one longest running task. Ali "back to sleep" I do not know the amount of time they will run. They are files that are being downloaded and I neither know the file size nor the download rate(in fact, the actual download happens externally). While I could use work unit of size 1 then problem then is I would be downloading N files at once and that will cause other problems if N is large(and sometimes it is). There should be a "work unit size" and a "max simultaneous workers". Then I could set the work unit size to 1 and say the max simultaneous workers to 8 to get 8 simultaneous downloads without stalling.
Re: parallel threads stalls until all thread batches are finished.
On Wednesday, 23 August 2023 at 13:03:36 UTC, Joe wrote: to download files from the internet. Are they particularly big files? You might consider using one of the other libs that does it all in one thread. (i ask about size cuz mine ive never tested doing big files at once, i usually use it for smaller things, but i think it can do it) The reason why this causes me problems is that the downloaded files, which are cashed to a temporary file, stick around and do not free up space(think of it just as using memory) and this can cause some problems some of the time. this is why im a lil worried about my thing, like do they have to be temporary files or can it be memory that is recycled?
Re: parallel threads stalls until all thread batches are finished.
On 8/25/23 14:27, j...@bloow.edu wrote: > "A work unit is a set of consecutive elements of range to be processed > by a worker thread between communication with any other thread. The > number of elements processed per work unit is controlled by the > workUnitSize parameter. " > > So the question is how to rebalance these work units? Ok, your question brings me back from summer hibernation. :) This is what I do: - Sort the tasks in decreasing time order; the ones that will take the most time should go first. - Use a work unit size of 1. The longest running task will start first. You can't get better than that. When I print some progress reporting, I see that most of the time N-1 tasks have finished and we are waiting for that one longest running task. Ali "back to sleep"
Re: parallel threads stalls until all thread batches are finished.
On Wednesday, 23 August 2023 at 14:43:33 UTC, Sergey wrote:
On Wednesday, 23 August 2023 at 13:03:36 UTC, Joe wrote:
I use
foreach(s; taskPool.parallel(files, numParallel))
{ L(s); } // L(s) represents the work to be done.
If you make for example that L function return “ok” in case
file successfully downloaded, you can try to use TaskPool.amap.
The other option - use std.concurrency probably.
I think I might know what is going on but not sure:
The tasks are split up in batches and each batch gets a thread.
What happens then is some long task will block it's entire batch
and there will be no re-balancing of the batches.
"A work unit is a set of consecutive elements of range to be
processed by a worker thread between communication with any other
thread. The number of elements processed per work unit is
controlled by the workUnitSize parameter. "
So the question is how to rebalance these work units?
E.g., when a worker thread is done with it's batch it should look
to help finish that batch rather than terminating and leaving all
the work for the last thread.
This seems like a flaw in the design. E.g., if one happens to
have n batches and every batch but one has tasks that finish
instantly then essentially one has no parallelization.
Re: parallel threads stalls until all thread batches are finished.
On Wednesday, 23 August 2023 at 14:43:33 UTC, Sergey wrote:
On Wednesday, 23 August 2023 at 13:03:36 UTC, Joe wrote:
I use
foreach(s; taskPool.parallel(files, numParallel))
{ L(s); } // L(s) represents the work to be done.
If you make for example that L function return “ok” in case
file successfully downloaded, you can try to use TaskPool.amap.
The other option - use std.concurrency probably.
Any idea why it is behaving the way it is?
Re: parallel threads stalls until all thread batches are finished.
On Wednesday, 23 August 2023 at 13:03:36 UTC, Joe wrote:
I use
foreach(s; taskPool.parallel(files, numParallel))
{ L(s); } // L(s) represents the work to be done.
If you make for example that L function return “ok” in case file
successfully downloaded, you can try to use TaskPool.amap.
The other option - use std.concurrency probably.
