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Subject: Re: [boost] [compute] Review
From: Gruenke,Matt (mgruenke_at_[hidden])
Date: 2015-01-01 18:41:45

-----Original Message-----
From: Boost [mailto:boost-bounces_at_[hidden]] On Behalf Of Jason Newton
Sent: Thursday, January 01, 2015 4:46
To: boost_at_[hidden]
Subject: Re: [boost] [compute] Review

> I'd be very interested in seeing a valid and direct comparison of a few common
> algorithms implemented in the same fashion in OpenCL and CUDA in addition
> library-to-library performance charts
> [here:]
> Boost.Compute has already - this might take away some of the fear from the
> research community of OpenCL vs CUDA esp given the strength of the Boost name.

The biggest issue I see with those performance comparisons is that they're not very realistic. While a direct comparisons of individual operation performance is certainly interesting, a more relevant metric would be to implement and compare solutions to real-world problems. This will expose various copying and synchronization overheads, which are doubtlessly of concern to many current GPGPU practitioners and potential Boost.Compute users.

> A few tidbits relating to the work other than that though:
> -One of the things I don't like is the scan operation recursively calls itself
> and reallocates memory a bunch of times - Bolt seems to have taken a better
> approach here which reduces the global memory usage too. I don't like
> additional memory allocations or things that could incur unnecessary/unexpected
> latencies if the problem changes size.

At the very least, documentation of the memory requirements might help users partition their data appropriately to avoid device memory exhaustion.



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