NVIDIA's DGX-2 system offers a unique architecture which connects 16 GPUs together via the high-speed NVLink interface, along with NVSwitch which enables unprecedented bandwidth between processors. This talk will take an in depth look at the properties of this system along with programming techniques to take maximum advantage of the system architecture.
CUDA 10.0, the latest major revision of the CUDA platform, was released in September and introduces the latest Turing GPU architecture and a host of new features. This talk presents all the details including a new graphs programming model, more flexible system support mechanisms and of course the new capabilities offered by the Turing GPU.
CUDA is NVIDIA''s parallel computing platform and programming model. You''ll learn about new programming model enhancements and performance improvements in the latest release of CUDA, preview upcoming GPU programming technology, and gain insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You''ll also learn about NVIDIA''s vision for CUDA and the challenges for the future of parallel software development.
Optimizing your code can be one of the most challenging tasks in GPU programming, but also one of the most rewarding: the performance difference between an initial version and well-tuned code can be a factor of 10 or more. Some optimizations can be quite straightforward while others require care and deep understanding of how the code is executing. A particular focus will be on optimization of the CPU part of your code, which is frequently overlooked even though it is often easier to tune and just as effective. Sometimes the biggest obstacle is just knowing what to look for, so we'll cover a range of techniques that everyone from beginners to CUDA ninjas might not have thought of before.
Deep Learning is delivering the future today, enabling computers to perform tasks once thought possible only in science fiction. Innovations such as autonomous vehicles, speech recognition and advances in medical imaging will transform the world as we know it. GPUs are at the core of this transformation, providing the engines that power Deep Learning. In this session, we'll discuss the software tools NVIDIA provides to unlock the power of Deep Learning on GPUs. We'll provide an overview of NVIDIA's Deep Learning Software, including cuDNN and DIGITS, and pointers to maximize your experience with Deep Learning at GTC.
NVIDIA provides tools that help you get the most out of your Android application. Come learn how to minimize your time to market while maximizing stability and performance. This session will cover native Android GPU debugging and profiling tools, CPU debugging and profiling tools, including Nsight Tegra, the premiere Android development for Microsoft Visual Studio.
Atomic memory operations provide powerful communication and coordination capabilities for parallel programs, including the well-known operations compare-and-swap and fetch-and-add. The atomic operations enable the creation of parallel algorithms and data structures that would otherwise be very difficult (or impossible) to express without them - for example: shared parallel data structures, parallel data aggregation, and control primitives such as semaphores and mutexes. In this talk we will use examples to describe atomic operations, explain how they work, and discuss performance considerations and pitfalls when using them.
This presentation looks into the features of NVIDIA's latest Kepler GPU architecture. Join us as one of CUDA's language architects explains what's new, why it's exciting, and demonstrates the power of Kepler GPU accelerators with a real-time cosmology simulation in full 3D.
The continuing evolution of the GPU brings with it new hardware capabilities and new functionality. Simultaneously, ongoing development of CUDA and its tools, libraries and ecosystem brings new features to the software stack as well. Come and learn from on of CUDA's programming model architects about what's new in the GPU, what's coming in the next release of CUDA, how it works, and how it all fits together.