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GTC ON-DEMAND

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Abstract:
CUDA is NVIDIA's parallel computing platform and programming model. In this talk, you'll learn about the new features in CUDA 9, including Cooperative Groups, an extension to the CUDA programming model for organizing groups of threads that helps you write efficient parallel algorithms that are safe, modular, and maintainable. You'll also learn about new features in CUDA that allow you to program the new Volta GPU architecture features such as Tensor Cores, providing the highest possible performance for deep learning training and inference. Finally, you'll get a preview of features and improvements coming to future releases of CUDA, and gain insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs.
CUDA is NVIDIA's parallel computing platform and programming model. In this talk, you'll learn about the new features in CUDA 9, including Cooperative Groups, an extension to the CUDA programming model for organizing groups of threads that helps you write efficient parallel algorithms that are safe, modular, and maintainable. You'll also learn about new features in CUDA that allow you to program the new Volta GPU architecture features such as Tensor Cores, providing the highest possible performance for deep learning training and inference. Finally, you'll get a preview of features and improvements coming to future releases of CUDA, and gain insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs.  Back
 
Topics:
Developer Tools, Artificial Intelligence and Deep Learning, HPC and Supercomputing
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7146
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Abstract:

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 will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.

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 will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.

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Topics:
Programming Languages, Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7132
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Abstract:

Emerging heterogeneous systems are opening up tons of programming opportunities. This panel will discuss the latest developments in accelerator programming where the programmers have a choice among OpenMP, OpenACC, CUDA and Kokkos for GPU programming. This panel will throw light on what would be the primary objective(s) for a choice of model, whether its availability across multiple platforms, its rich feature set or its applicability for a certain type of scientific code or compilers' stability or other factors. This will be an interactive Q/A session where participants can discuss their experiences with programming model experts and developers.

Emerging heterogeneous systems are opening up tons of programming opportunities. This panel will discuss the latest developments in accelerator programming where the programmers have a choice among OpenMP, OpenACC, CUDA and Kokkos for GPU programming. This panel will throw light on what would be the primary objective(s) for a choice of model, whether its availability across multiple platforms, its rich feature set or its applicability for a certain type of scientific code or compilers' stability or other factors. This will be an interactive Q/A session where participants can discuss their experiences with programming model experts and developers.

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Topics:
HPC and Supercomputing, Programming Languages
Type:
Panel
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7564
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Abstract:

The revolutionary NVIDIA® Pascal™ architecture is purpose-built to be the engine of computers that learn, see, and simulate our world—a world with an infinite appetite for computing. Pascal incorporates ground-breaking technologies to deliver the highest absolute performance for HPC, technical computing, deep learning, and many computationally intensive data center workloads. In this talk you'll see how Pascal GPUs provides extreme performance and scaling using the new NVLink high-speed GPU interconnect, HBM2 stacked memory for massive bandwidth, and massive computational throughput for artificial intelligence with new 16-bit floating point instructions.

The revolutionary NVIDIA® Pascal™ architecture is purpose-built to be the engine of computers that learn, see, and simulate our world—a world with an infinite appetite for computing. Pascal incorporates ground-breaking technologies to deliver the highest absolute performance for HPC, technical computing, deep learning, and many computationally intensive data center workloads. In this talk you'll see how Pascal GPUs provides extreme performance and scaling using the new NVLink high-speed GPU interconnect, HBM2 stacked memory for massive bandwidth, and massive computational throughput for artificial intelligence with new 16-bit floating point instructions.

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Topics:
HPC and AI
Type:
Talk
Event:
AI Conference Australia
Year:
2016
Session ID:
AUS6103
Streaming:
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Abstract:

This talk will introduce participants to the library and its capabilities, review recent results, detail improvements to the library, and discuss future directions.

This talk will introduce participants to the library and its capabilities, review recent results, detail improvements to the library, and discuss future directions.

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Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2016
Session ID:
SC6104
Streaming:
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Abstract:

The revolutionary NVIDIA® Pascal™ architecture is purpose-built to be the engine of computers that learn, see, and simulate our world—a world with an infinite appetite for computing. Pascal incorporates ground-breaking technologies to deliver the highest absolute performance for HPC, technical computing, deep learning, and many computationally intensive datacenter workloads. In this talk you'll see how new the new Pascal architecture provides extreme performance and scaling using the new NVLink high-speed GPU interconnect, HBM2 stacked memory for massive bandwidth, and high computational throughput for artificial intelligence with new 16-bit floating point instructions. You'll also learn how Unified Memory in CUDA benefits from Pascal's new Page Migration Engine.

The revolutionary NVIDIA® Pascal™ architecture is purpose-built to be the engine of computers that learn, see, and simulate our world—a world with an infinite appetite for computing. Pascal incorporates ground-breaking technologies to deliver the highest absolute performance for HPC, technical computing, deep learning, and many computationally intensive datacenter workloads. In this talk you'll see how new the new Pascal architecture provides extreme performance and scaling using the new NVLink high-speed GPU interconnect, HBM2 stacked memory for massive bandwidth, and high computational throughput for artificial intelligence with new 16-bit floating point instructions. You'll also learn how Unified Memory in CUDA benefits from Pascal's new Page Migration Engine.

  Back
 
Topics:
Healthcare and Life Sciences, Healthcare and Life Sciences, HPC and AI
Type:
Talk
Event:
GTC Washington D.C.
Year:
2016
Session ID:
DCS16143
Streaming:
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Topics:
HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6176
Streaming:
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Abstract:
CUDA is NVIDIA's parallel computing platform and programming model. In this talk you'll learn about new features and performance improvements in CUDA 8. In this talk you'll hear about features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.
CUDA is NVIDIA's parallel computing platform and programming model. In this talk you'll learn about new features and performance improvements in CUDA 8. In this talk you'll hear about features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.  Back
 
Topics:
Programming Languages, Tools & Libraries, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6224
Streaming:
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Abstract:
CUDA is NVIDIA's parallel computing platform and programming model. In this talk you'll learn how new support for C++11 in CUDA 7, along with new features and performance improvements in the Thrust C++ parallel algorithms library, and support for runtime compilation, makes parallel C++ more productive than ever. CUDA 7 also includes cuSOLVER, a new direct linear solver library, as well as new features and improved performance in other CUDA libraries. In this talk you'll hear about these features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.
CUDA is NVIDIA's parallel computing platform and programming model. In this talk you'll learn how new support for C++11 in CUDA 7, along with new features and performance improvements in the Thrust C++ parallel algorithms library, and support for runtime compilation, makes parallel C++ more productive than ever. CUDA 7 also includes cuSOLVER, a new direct linear solver library, as well as new features and improved performance in other CUDA libraries. In this talk you'll hear about these features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.  Back
 
Topics:
Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5820
Streaming:
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Abstract:
CUDA is NVIDIA's parallel computing platform and programming model. CUDA 6 dramatically increases developer productivity with the introduction of Unified Memory, which simplifies memory management by automatically migrating data between the CPU and GPU. Unified Memory and other new features in CUDA tools and libraries make GPU computing easier than ever before. In this talk you'll hear about these features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.
CUDA is NVIDIA's parallel computing platform and programming model. CUDA 6 dramatically increases developer productivity with the introduction of Unified Memory, which simplifies memory management by automatically migrating data between the CPU and GPU. Unified Memory and other new features in CUDA tools and libraries make GPU computing easier than ever before. In this talk you'll hear about these features and get insight into the philosophy driving the development of CUDA and how it will take advantage of current and future GPUs. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.  Back
 
Topics:
Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4830
Streaming:
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Abstract:

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. Learn how powerful new features in CUDA 6 make GPU computing easier than ever, helping you accelerate more of your application with much less code.

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. Learn how powerful new features in CUDA 6 make GPU computing easier than ever, helping you accelerate more of your application with much less code.

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Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2013
Session ID:
SC3108
Streaming:
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Abstract:

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. Learn how powerful new features in CUDA 6 make GPU computing easier than ever, helping you accelerate more of your application with much less code.

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. Learn how powerful new features in CUDA 6 make GPU computing easier than ever, helping you accelerate more of your application with much less code.

  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2013
Session ID:
SC3120
Streaming:
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Abstract:

The future of computing is parallelism, and NVIDIA's goal for CUDA is to create an accessible and pervasive platform for diverse, high performance parallel computing. In this talk I will share our vision for the future of the CUDA platform and programming model, and present specific features of current and future CUDA releases that are important steps toward that future. CUDA provides a programming model that makes it easy for programmers to expose large amounts of parallelism in their applications, but I'll talk about ways that we are making heterogeneous computing software easier to write, optimize and maintain. I'll demonstrate how we are enabling the CUDA platform to support a broader range of programming languages and libraries. And, I will talk about technologies aimed at making CUDA applications more efficiently scale to large parallel systems.

The future of computing is parallelism, and NVIDIA's goal for CUDA is to create an accessible and pervasive platform for diverse, high performance parallel computing. In this talk I will share our vision for the future of the CUDA platform and programming model, and present specific features of current and future CUDA releases that are important steps toward that future. CUDA provides a programming model that makes it easy for programmers to expose large amounts of parallelism in their applications, but I'll talk about ways that we are making heterogeneous computing software easier to write, optimize and maintain. I'll demonstrate how we are enabling the CUDA platform to support a broader range of programming languages and libraries. And, I will talk about technologies aimed at making CUDA applications more efficiently scale to large parallel systems.

  Back
 
Topics:
Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3500
Streaming:
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Abstract:

NVIDIA's CUDA C/C++ Compiler (NVCC) is based on the widely used LLVM open source compiler infrastructure. This open foundation enables developers to create or extend programming languages with support for GPU acceleration using the CUDA Compiler SDK. In this talk you will learn how to use the NVIDIA Compiler SDK to generate high-performance parallel code for NVIDIA GPUs.

NVIDIA's CUDA C/C++ Compiler (NVCC) is based on the widely used LLVM open source compiler infrastructure. This open foundation enables developers to create or extend programming languages with support for GPU acceleration using the CUDA Compiler SDK. In this talk you will learn how to use the NVIDIA Compiler SDK to generate high-performance parallel code for NVIDIA GPUs.

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Topics:
Programming Languages
Type:
Talk
Event:
Supercomputing
Year:
2012
Session ID:
SC2019
Streaming:
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Abstract:

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. In this talk you will learn about powerful new features of CUDA 5 and the Kepler GPU architecture, including CUDA Dynamic Parallelism, CUDA device code linking, and the new NSight Eclipse Edition.

The performance and efficiency of CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and services, have helped make GPU computing a leading HPC technology. In this talk you will learn about powerful new features of CUDA 5 and the Kepler GPU architecture, including CUDA Dynamic Parallelism, CUDA device code linking, and the new NSight Eclipse Edition.

  Back
 
Topics:
Programming Languages
Type:
Talk
Event:
Supercomputing
Year:
2012
Session ID:
SC2020
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Abstract:

CUDA, NVIDIA's platform for parallel computing, has grown rapidly in the past 5 years. The performance and efficiency of software built on CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and service providers, have helped make GPU computing a leading HPC technology. CUDA 5 and the Kepler GPU architecture don't just increase application performance; they enable a more powerful parallel programming model that expands the possibilities of GPU computing, and language features that improve programmer productivity. In this talk you'll hear about these revolutionary features and get insight into the philosophy driving the development of new CUDA hardware and software. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.

CUDA, NVIDIA's platform for parallel computing, has grown rapidly in the past 5 years. The performance and efficiency of software built on CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and service providers, have helped make GPU computing a leading HPC technology. CUDA 5 and the Kepler GPU architecture don't just increase application performance; they enable a more powerful parallel programming model that expands the possibilities of GPU computing, and language features that improve programmer productivity. In this talk you'll hear about these revolutionary features and get insight into the philosophy driving the development of new CUDA hardware and software. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.

  Back
 
Topics:
Programming Languages
Type:
Talk
Event:
GTC Silicon Valley
Year:
2012
Session ID:
S2641
Streaming:
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Speakers:
Mark Harris
- NVIDIA
Abstract:
Learn about the importance of optimized data-parallel algorithm primitives as building blocks for efficient real-world applications. Fundamental parallel algorithms like sorting, parallel reduction, and parallel scan are key components in a wide range of applications from video games to serious science. This session will cover the state of the art in data-parallel primitive algorithms for GPUs. Starting with an explanation of the purpose and applications of the algorithms, we will discuss key algorithm design principles, demonstrate current open source algorithm libraries for GPUs (CUDPP and Thrust), describe optimizations using new features in the Fermi architecture, and explore future directions.
Learn about the importance of optimized data-parallel algorithm primitives as building blocks for efficient real-world applications. Fundamental parallel algorithms like sorting, parallel reduction, and parallel scan are key components in a wide range of applications from video games to serious science. This session will cover the state of the art in data-parallel primitive algorithms for GPUs. Starting with an explanation of the purpose and applications of the algorithms, we will discuss key algorithm design principles, demonstrate current open source algorithm libraries for GPUs (CUDPP and Thrust), describe optimizations using new features in the Fermi architecture, and explore future directions.  Back
 
Topics:
Developer - Algorithms, Tools & Libraries, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S102084
Streaming:
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