Postgres on the GPU
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Postgres on the GPU
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Re: Postgres on the GPU
#2NVidia's CUDA only (for now?)
Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
Re: Postgres on the GPU
#3NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
One reason why lots of things typically use CUDA is because NVidia makes datacenter rackmounted GPU gear. So there is no need to run generically if that is the only available "production" hardware.
Re: Postgres on the GPU
#4NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
there are matrix multiplication routines developed for CUDA. OpenCL you would have to do everything from the ground up. So Nvidia gave everyone a head start for numerical computation, and that edge has ever since snowballed.
Re: Postgres on the GPU
#5NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
Try programming in both CUDA and OpenCL and see which one you would choose.
Re: Postgres on the GPU
#6Really, really cool!
I've toyed with the idea of doing pattern matching (and graph rewriting) on the GPU before but this looks like it's much more advanced than I thought was feasible.
I'm surprised they went with CUDA instead of OpenCL though. CUDA is proprietary NVidea technology and does not work for non-NVidea devices.
Re: Postgres on the GPU
#7NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
There are probably a lot of factors. I worked on CUDA code for around a year, and used to understand the landscape pretty well, but if I were to start a high-performance computing project today I'd probably take my lumps and go with OpenCL. There would be a lot of lumps.
Firstly, CUDA is just more mature; there is a very large and well-established set of libraries for a lot of common operations, there is a decent sized community, and Nvidia even produces specialized hardware (Tesla cards) designed just for CUDA.
Second, all that generic-ness of OpenCL doesn't come for free. With Nvidia, you're just working with one architecture; CUDA cards. Optimizing your kernels is much easier. OpenCL is just generically parallel, so you could have any sort of crazy heterogeneous high-performance computing environment you have to fiddle with (any number of CPU's with different chipsets and any number of GPU's with different chipsets).
I haven't used OpenCL myself, but almost purely anecdotally I have heard many people say that CUDA is often slightly faster[1] and the code is easier to write.
TL;DR: CUDA sacrifices flexibility for ease of development and performance gains. OpenCL wants to be everything for everyone, and comes with the typical burdens.
[1]: Maybe this is a result of OpenCL being more generic and so harder to optimize.
Re: Postgres on the GPU
#8NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
You're preaching to the choir. Looks like NEC funded this.
NVidia seems to be the preferred hardware for institutions/big companies. I'm not sure if this is because NVidia's architecture is better for supercomputers or if they're simply better at marketing to those types of customers
NVidia funds a lot of academics in my space, and I've found academia to be very anti-open source for those reasons, which amuses me greatly.
Case in point, Matlab. Why is this taught in a world with Python/Numpy/MatplotLib?
Re: Postgres on the GPU
#9NVidia's CUDA only (for now?) Anyone can explain why opensource projects embrace CUDA over OpenCL? As I understand OpenCL is more generic API which could be potentially used with CPUs and GPUs.
You're preaching to the choir. Looks like NEC funded this. NVidia seems to be the preferred hardware for institutions/big companies. I'm not sure if this is because NVidia's architecture is better for supercomputers or if they're simply better at marketing to those types of customers NVidia funds a lot of academics in my space, and I've found academia to be very anti-open source for those reasons, which amuses me gre…
Matlab seems like inertia/culture to me: it's the longtime de-facto standard in engineering. Since it's what everyone uses, it's got packages for everything, and papers will often come with prototype Matlab implementations. Roughly like the cultural position R holds in statistics. Matlab's hold on engineering is also bolstered by its widespread use in industry: students want to learn it, because it's what their future employers use, and professors / research scientists like to use it because it's what their industrial collaborators use.
In my area of CS (artificial intelligence) it seems considerably less popular. I don't really remember how to use it, since the last time I used it seriously was in some engineering (but not CS) courses in undergrad.
Re: Postgres on the GPU
#10Earlier quoted context omitted.
You're preaching to the choir. Looks like NEC funded this. NVidia seems to be the preferred hardware for institutions/big companies. I'm not sure if this is because NVidia's architecture is better for supercomputers or if they're simply better at marketing to those types of customers NVidia funds a lot of academics in my space, and I've found academia to be very anti-open source for those reasons, which amuses me gre…
Matlab seems like inertia/culture to me: it's the longtime de-facto standard in engineering. Since it's what everyone uses, it's got packages for everything, and papers will often come with prototype Matlab implementations. Roughly like the cultural position R holds in statistics. Matlab's hold on engineering is also bolstered by its widespread use in industry: students want to learn it, because it's what their futur…
In addition, the MathWorks have so far managed not too screw up too badly and are keeping Matlab up to date. (They are definitely quite nice as an employer.)