They ran this on an FPGA, does that not count as hardware? Or do you want to go to all of the open-source hardware communities and tell them what they do is not actually open-source hardware?
Huh? They've done an incredible job here. Just because you didn't give them $100k for them to do a tape-out doesn't mean they didn't create the first open-source GPU.
This is just about modeling a gpu architecture...
There's a HUGE difference between a simulator like GPGPU-SIM and something like this, which is doing actual RTL and gate-level simulation using the actual Verilog RTL.
OpenCL is an open standard, but there is not yet an open source implementation.
Thanks for clarifying to everyone for me.
I was in a hurry and misspoke. I was trying to imply that it wasn't tied to a single company/entity like CUDA, but rather a consortium of industry players, and "open-source" is what my fingers typed, instead of "open standard." Gah.
. And no law is forcing Steve Jobs to expose his medical history, nor does any corporation or individual have the power to legally force him to release this information. Apple cannot cite stock price losses as damages. They are also not required to present his health information to any outside entity, in accordance with his legal rights to protect that information. But I don't see where they are. He's reacting to negative articles and political developments both inside and outside his company, and his legal rights have nothing to do with these things.
Actually, I thought the entire point of this discussion *was* whether or not Jobs had the legal obligation to disclose his health.
If the law says that you must disclose all relevant information to the performance of the company, and Jobs's health has a drastic effect on his performance, one could make the legal case that Jobs must therefore - according to the law - disclose his health.
IANAL, and I barely RTFA, but that's what I gathered the discussion was about. But beyond that, your point is valid - a right doesn't prevent negative repercussions from happening to you.
Agreed. I did not read a *single* book for a EECS course. In fact, I cannot think of a single CS course that even mandated any reading. I will admit though that one of the more interesting classes I took provided two or three research papers every week. Not mandatory, but they were interesting enough to warrant reading. Stuff like the Niagra papers, Supralinear Speedups using Intel Quadcores, and the Cosmic cube.
I think it's great to see that we can finally start using GPUs to do things beyond gaming, but I also don't see it as the Great Second Coming of high-speed computing.
GPUs are designed to tackle only one kind of problem, and a highly parallel problem at that. If you are a researcher and you can see huge gains in performance by using GPUs, then great! But GPUs are hardly general purpose, and will simply not address most of our computing needs.
I see the rise of GPUs as similiar to computing in the 60's(?). Figure out what kind of software you need to run, and then design a computing platform around it. If you need to perform small operations on a highly parallel data structure, then a GPU cluster is an excellent way to go.
-One beginning computer architect's opinion
Slashdot Mirror
They ran this on an FPGA, does that not count as hardware? Or do you want to go to all of the open-source hardware communities and tell them what they do is not actually open-source hardware?
This is just about modeling a gpu architecture...
There's a HUGE difference between a simulator like GPGPU-SIM and something like this, which is doing actual RTL and gate-level simulation using the actual Verilog RTL.
I don't see that they have a working chip yet.
Yes, it's real silicon. There are 8 silicon implementations so far (from Berkeley at least, not from LowRISC). - Berkeley RISC-V user.
OpenCL is an open standard, but there is not yet an open source implementation.
Thanks for clarifying to everyone for me. I was in a hurry and misspoke. I was trying to imply that it wasn't tied to a single company/entity like CUDA, but rather a consortium of industry players, and "open-source" is what my fingers typed, instead of "open standard." Gah.
Open CL is the open source CUDA alternative. http://en.wikipedia.org/wiki/OpenCL
. And no law is forcing Steve Jobs to expose his medical history, nor does any corporation or individual have the power to legally force him to release this information. Apple cannot cite stock price losses as damages. They are also not required to present his health information to any outside entity, in accordance with his legal rights to protect that information. But I don't see where they are. He's reacting to negative articles and political developments both inside and outside his company, and his legal rights have nothing to do with these things.
Actually, I thought the entire point of this discussion *was* whether or not Jobs had the legal obligation to disclose his health.
If the law says that you must disclose all relevant information to the performance of the company, and Jobs's health has a drastic effect on his performance, one could make the legal case that Jobs must therefore - according to the law - disclose his health.
IANAL, and I barely RTFA, but that's what I gathered the discussion was about. But beyond that, your point is valid - a right doesn't prevent negative repercussions from happening to you.
Agreed. I did not read a *single* book for a EECS course. In fact, I cannot think of a single CS course that even mandated any reading. I will admit though that one of the more interesting classes I took provided two or three research papers every week. Not mandatory, but they were interesting enough to warrant reading. Stuff like the Niagra papers, Supralinear Speedups using Intel Quadcores, and the Cosmic cube.
I think it's great to see that we can finally start using GPUs to do things beyond gaming, but I also don't see it as the Great Second Coming of high-speed computing. GPUs are designed to tackle only one kind of problem, and a highly parallel problem at that. If you are a researcher and you can see huge gains in performance by using GPUs, then great! But GPUs are hardly general purpose, and will simply not address most of our computing needs. I see the rise of GPUs as similiar to computing in the 60's(?). Figure out what kind of software you need to run, and then design a computing platform around it. If you need to perform small operations on a highly parallel data structure, then a GPU cluster is an excellent way to go. -One beginning computer architect's opinion