Nvidia announces CUDA 4.0

http://pressroom.nvidia.com/easyir/customrel.do?easyirid=A0D622CE9F579F09&version=live&prid=726171&releasejsp=release_157&xhtml=true

by m0nastic • 15 years ago

41 26 15 years ago

pressroom.nvidia.com

m0nastic• 15 years ago

The listed link is PR, but here is also some more details about what 4.0 contains:

http://developer.nvidia.com/object/cuda_4_0_RC_downloads.htm...

bryanlarsen• 15 years ago

anandtech has some good info, too: http://www.anandtech.com/show/4198/nvidia-announces-cuda-40

tmurray7• 15 years ago

Been working on the API improvements for this for quite a while now. If there are any questions I can answer, I'll tell you whatever I can.

(edit: in case it's not obvious, I work for NVIDIA on CUDA)

lrm242• 15 years ago

I haven't done any CUDA programming, however I have wanted to dive in. I've been to some conferences where the breakpoint between whether CUDA gives enough benefit to the computation is largely driven by time to load a dataset into memory on the GPU. From what I've been told this has limited the use of CUDA to batch processing on large scale datasets. Is this still a limitation?

tmurray7• 15 years ago

PCIe can be a limitation, but there are a lot of ways to amortize the latency of copying data to/from the GPU. Overlapping transfers with kernels, direct load/store from system memory to a kernel, multiple kernels running on the chip at the same time--there are a lot of things you can do. But in general, you're looking at a runtime of at least a few hundred microseconds before you're going to be able to get a benefit from the GPU.

marshray• 15 years ago

Congrats on your upcoming major release! I'm sure it was a lot of work.

I'm a detail freak so I worry about this kind of thing more than most, but wouldn't a unified address space tend to hide large bus transfers from the programmer?

Will the APIs still let you anticipate where the costs are, or are developers dependent on Windows-only profiling tools?

tmurray7• 15 years ago

It's not a true unified address space in the way I think you're getting at. We carve out the address space, but you can't just directly dereference a GPU pointer from CPU code or vice-versa. What we guarantee is that you can determine the location of a pointer based only on the value of the pointer so you can make the appropriate API calls to do a copy if necessary.

iskander4• 15 years ago

One thing that completely puzzles me: How does dynamic memory allocation/deallocation in GPU kernels work? Also, will the programmer be able to use virtual functions in CUDA kernels? If so, does the usual thinking about warp divergence apply? That is--- should all threads in a warp ideally be calling the same function address?

tmurray7• 15 years ago

I think there's some preallocated memory for dynamic allocations from the device. As far as I know virtual functions work as well, and the usual thinking about warp divergence does apply.

maximilian• 15 years ago

Have you done any benchmarks regarding inter-GPU memory bandwidth (i.e. GPU1->GPU2) vs. GPU1->host->GPU2? I am working on multi-gpu problems, which are often throttled by bandwidth limitations. Does the new SDK have examples of this and the new unified memory architecture (which looks handy)?

matclayton• 15 years ago

If you are interested in GPU coding, checkout www.tidepowerd.com for a .net cross vendor system, also falls back to CPU and they are a startup :)

ericxtang• 15 years ago

CUDA has come a long way since it's birth as a student project.

iskander4• 15 years ago

Who wrote the first version? I always assumed it was nvidia's version of Brook.

tmurray7• 15 years ago

CUDA and BrookGPU share the same creator, but there's not really anything else in common. The programming models are fundamentally different (multi-level memory hierarchy with sharing of local data with fast synchronization versus pure streaming).

babs474• 15 years ago

Is anybody who is interested in CUDA also interested in the idea of GPGPU computation in the browser using webGL? Here is a link to a proof of concept I did a while ago http://learningwebgl.com/blog/?p=1828

I think the concept is pretty compelling but I don't get that much traction when I bring it up. Any thoughts?

ciupicri• 15 years ago

Seeing all the buzz about CUDA I can not stop wondering if OpenCL has any future. Does it?

vilya• 15 years ago

It does, I think. OpenCL's trump card is that it works on non-Nvidia devices as well. I believe that'll ultimately be enough for it to win out, despite the technical merit being in favour of CUDA right now.

phlux3• 15 years ago

So forgive my ignorance, but would the following be of value in a system design/architecture.

(I dont know what type of cards you have which you would use in this, such as a multi-GPU cored PCI-e card, so in my ignorance, I will assume these exist and are separate from a traditional "video card")

I would be interested to see a system, as a brick, which has a mobo with multiple PCI-e slots, as many as one can get then fill it with both GPU based cards, as well as Fusion IO cards that provide extremely fast IOPs on the storage side. The main CPU in the box, is effectively used to boot the OS - all the other processing and IOPs occur on the GPUs and the Fusion IO cards as data storage and caching...

Is this a realistic idea?

lwat2• 15 years ago

GPUs can't run arbitrary code. You have to code specifically for them. They don't run operating systems or web servers or whatever. These are for massively parallel mathematical computations, not for system calls and threads and stuff like that.

phlux3• 15 years ago

Right, I do know that --

What Iam saying is that a system that uses both GPUs and the fusion IO cards would seem to provide a kickass platform for mass computation on lots of data in a small form factor.

Nvidia announces CUDA 4.0

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