If you had a chance to read or take part in our live chat with David Kirk, then you likely saw all the great questions we received. In fact, there were so many David didn’t have time to answer all of them during the one-hour chat. Not to worry, though, we were able to circle back with David and get his take on a few more of your questions. You can read his responses below.
Stay tuned to the blog for updates on when the next GPU Technology Conference (GTC) live chat will take place. And, just as a reminder, GTC is just around the corner so register now to benefit from the early-bird rates.
Question from lawless:
Do you think processor architectures like this are going to replace traditional CPU's?
I think what you’ll see are more and more systems designed to use the GPU for parallel processing, while continuing to use a CPU type processor to run the operating system and manage basic serial functionality. This is a view shared by many in the high performance computing space, such as Jack Dongarra at the University of Tennessee who has been quoted as saying that future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs.
Question from Benjamin:
Recently a new book called CUDA by Example was launched, could you talk about this book and how it could be a complement of your book?
I see them as complementary. The book I wrote with Dr. Hwu, Programming Massively Parallel Processors: A Hands-on Approach, is designed for use in the classroom and as a reference for computing professionals. The new CUDA by Example book provides a great self-paced introduction to parallel programming, and CUDA API information using source code examples that help programmers who are just getting started learn by implementing examples for each concept covered in the book. So, both books can be effectively used together, or separately.
Question from Allan:
The question is whether NVIDIA sees their primary role as being the caretaker of the "PTX" opcodes and the CUDA platform with the market building on these technologies or will NVIDIA consider developing and promoting additional new GPU-leveraging software?
NVIDIA is already investing in software solutions that leverage the general-purpose GPU computing capabilities of GPUs. Examples include our suite of application acceleration engines or “AXEs” available as well as several interesting solutions from our mental images division. More at: