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A Comprehensive Suite of Compilers, Libraries and Tools for HPC

The NVIDIA HPC Software Development Kit (SDK) includes the proven compilers, libraries and software tools essential to maximizing developer productivity and the performance and portability of HPC applications.

The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC® directives, and CUDA®. GPU-accelerated math libraries maximize performance on common HPC algorithms, and optimized communications libraries enable standards-based multi-GPU and scalable systems programming. Performance profiling and debugging tools simplify porting and optimization of HPC applications, and containerization tools enable easy deployment on-premises or in the cloud. With support for NVIDIA GPUs and Arm, OpenPOWER, or x86-64 CPUs running Linux, the HPC SDK provides the tools you need to build NVIDIA GPU-accelerated HPC applications.

Why Use the NVIDIA HPC SDK?

Performance

Widely used HPC applications, including VASP, Gaussian, ANSYS Fluent, GROMACS, and NAMD, use CUDA, OpenACC, and GPU-accelerated math libraries to deliver breakthrough performance to their users. You can use these same software tools to GPU-accelerate your applications and achieve dramatic speedups and power efficiency using NVIDIA GPUs.

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Portability

Build and optimize applications for over 99 percent of today’s Top500 systems, including those based on NVIDIA GPUs or x86-64, Arm or OpenPOWER CPUs. You can use drop-in libraries, C++17 parallel algorithms and OpenACC directives to GPU accelerate your code and ensure your applications are fully portable to other compilers and systems. Download virtual box for macos.

Productivity

Maximize science and engineering throughput and minimize coding time with a single integrated suite that allows you to quickly port, parallelize and optimize for GPU acceleration, including industry-standard communication libraries for multi-GPU and scalable computing, and profiling and debugging tools for analysis.

Support for Your Favorite Programming Languages

C++17 Parallel Algorithms

C++17 parallel algorithms enable portable parallel programming using the Standard Template Library (STL). The NVIDIA HPC SDK C++ compiler supports full C++17 on CPUs and offloading of parallel algorithms to NVIDIA GPUs, enabling GPU programming with no directives, pragmas, or annotations. Programs that use C++17 parallel algorithms are readily portable to most C++ implementations for Linux, Windows, and macOS.

Fortran 2003 Compiler

The NVIDIA Fortran compiler supports Fortran 2003 and many features of Fortran 2008. With support for OpenACC and CUDA Fortran on NVIDIA GPUs, and SIMD vectorization, OpenACC and OpenMP for multicore x86-64, Arm, and OpenPOWER CPUs, it has the features you need to port and optimize your Fortran applications on today’s heterogeneous GPU-accelerated HPC systems.

OpenACC Directives

NVIDIA Fortran, C, and, C++ compilers support OpenACC directive-based parallel programming for NVIDIA GPUs and multicore CPUs. Over 200 HPC application ports have been initiated or enabled using OpenACC, including production applications like VASP, Gaussian, ANSYS Fluent, WRF, and MPAS. OpenACC is the proven performance-portable directives solution for GPUs and multicore CPUs.

Key Features

GPU Math Libraries

The cuBLAS and cuSOLVER libraries provide GPU-optimized and multi-GPU implementations of all BLAS routines and core routines from LAPACK, automatically using NVIDIA GPU Tensor Cores where possible. cuFFT includes GPU-accelerated 1D, 2D, and 3D FFT routines for real and complex data, and cuSPARSE provides basic linear algebra subroutines for sparse matrices. These libraries are callable from CUDA and OpenACC programs written in C, C++ and Fortran.

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Optimized for Tensor Cores

NVIDIA GPU Tensor Cores enable scientists and engineers to dramatically accelerate suitable algorithms using mixed precision or double precision. The NVIDIA HPC SDK math libraries are optimized for Tensor Cores and multi-GPU nodes to deliver the full performance potential of your system with minimal coding effort. Using the NVIDIA Fortran compiler, you can leverage Tensor Cores through automatic mapping of transformational array intrinsics to the cuTENSOR library.

Optimized for Your CPU

Heterogeneous HPC servers use GPUs for accelerated computing and multicore CPUs based on the x86-64, OpenPOWER or Arm instruction set architectures. NVIDIA compilers and tools are supported on all of these CPUs, and all compiler optimizations are fully enabled on any CPU that supports them. With uniform features, command-line options, language implementations, programming models, and tool and library user interfaces across all supported systems, the NVIDIA HPC SDK simplifies the developer experience in diverse HPC environments.

Multi-GPU Programming

Price of djay pro 2. The NVIDIA Collective Communications Library (NCCL) implements highly optimized multi-GPU and multi-node collective communication primitives using MPI-compatible all-gather, all-reduce, broadcast, reduce, and reduce-scatter routines to take advantage of all available GPUs within and across your HPC server nodes. NVSHMEM implements the OpenSHMEM standard for GPU memory and provides multi-GPU and multi-node communication primitives that can be initiated from a host CPU or GPU and called from within a CUDA kernel. Python programming language mac.

Scalable Systems Programming

MPI is the standard for programming distributed-memory scalable systems. The NVIDIA HPC SDK includes a CUDA-aware MPI library based on Open MPI with support for GPUDirect™ so you can send and receive GPU buffers directly using remote direct memory access (RDMA), including buffers allocated in CUDA Unified Memory. CUDA-aware Open MPI is fully compatible with CUDA C/C++, CUDA Fortran and the NVIDIA OpenACC compilers.

Nsight Performance Profiling

Nsight™ Systems provides system-wide visualization of application performance on HPC servers and enables you to optimize away bottlenecks and scale parallel applications across multicore CPUs and GPUs. Nsight Compute allows you to deep dive into GPU kernels in an interactive profiler for GPU-accelerated applications via a graphical or command-line user interface, and allows you to pinpoint performance bottlenecks using the NVTX API to directly instrument regions of your source code.

Deploy Anywhere

Containers simplify software deployment by bundling applications and their dependencies into portable virtual environments. The NVIDIA HPC SDK includes instructions for developing, profiling, and deploying software using the HPC Container Maker to simplify the creation of container images. The NVIDIA Container Runtime enables seamless GPU support in virtually all container frameworks, including Docker and Singularity.

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What Users are Saying

“On Perlmutter, we need Fortran, C and C++ compilers that support all the programming models our users need and expect on NVIDIA GPUs and AMD EPYC CPUs — MPI, OpenMP, OpenACC, CUDA and optimized math libraries. The NVIDIA HPC SDK checks all of those boxes.”

– Nicholas Wright, NERSC Chief Architect

HPC Compilers Support Services

HPC Compiler Support Services provide access to NVIDIA technical experts, including:

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• Paid technical support for the NVFORTRAN, NVC++ and NVC compilers.
• Help with installation and usage of NVFORTRAN, NVC++ and NVC compilers.
• Confirmation of bug reports, prioritization of bug fixes above those from non-paid users.
• Help with temporary workarounds for confirmed compiler bugs.
• Access to release archives.
• More details in the End Customer Terms & Conditions.

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Get Started

• Already have an active support contract? Login to the support portal.
• Interested in purchasing these support services? Contact us.
• Existing customers: want to renew your contract? Contact us.
• Questions? Contact enterpriseservices@nvidia.com.

Resources

• Developer Blog: Accelerating Standard C++ with GPUs Using stdpar
• Developer Blog: Bringing Tensor Cores to Standard Fortran
• Related libraries and software:

Get Started

With an all-new design that looks great on macOS Big Sur, Xcode 12 has customizable font sizes for the navigator, streamlined code completion, and new document tabs. Xcode 12 builds Universal apps by default to support Mac with Apple Silicon, often without changing a single line of code.

Designed for macOS Big Sur.

Xcode 12 looks great on macOS Big Sur, with a navigator sidebar that goes to the top of the window and clear new toolbar buttons. The navigator defaults to a larger font that’s easier to read, while giving you multiple size choices. New document tabs make it easy to create a working set of files within your workspace.

Document tabs.

The new tab model lets you open a new tab with a double-click, or track the selected file as you click around the navigator. You can re-arrange the document tabs to create a working set of files for your current task, and configure how content is shown within each tab. The navigator tracks the open files within your tabs using strong selection.

Navigator font sizes.

The navigator now tracks the system setting for “Sidebar icon size” used in Finder and Mail. You can also choose a unique font size just for Xcode within Preferences, including the traditional dense information presentation, and up to large fonts and icon targets.

Code completion streamlined.

A new completion UI presents only the information you need, taking up less screen space as you type. And completions are presented much faster, so you can keep coding at maximum speed.

Redesigned organizer.

An all-new design groups all critical information about each of your apps together in one place. Choose any app from any of your teams, then quickly navigate to inspect crash logs, energy reports, and performance metrics, such as battery consumption and launch time of your apps when used by customers.

SwiftUI

SwiftUI offers new features, improved performance, and the power to do even more, all while maintaining a stable API that makes it easy to bring your existing SwiftUI code forward into Xcode 12. A brand new life cycle management API for apps built with SwiftUI lets you write your entire app in SwiftUI and share even more code across all Apple platforms. And a new widget platform built on SwiftUI lets you build widgets that work great on iPad, iPhone, and Mac. Your SwiftUI views can now be shared with other developers, and appear as first-class controls in the Xcode library. And your existing SwiftUI code continues to work, while providing faster performance, better diagnostics, and access to new controls.

Universal app ready.

Xcode 12 is built as a Universal app that runs 100% natively on Intel-based CPUs and Apple Silicon for great performance and a snappy interface.* It also includes a unified macOS SDK that includes all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.

Updated automatically

When you open your project in Xcode 12, your app is automatically updated to produce release builds and archives as Universal apps. When you build your app, Xcode produces one binary “slice” for Apple Silicon and one for the Intel x86_64 CPU, then wraps them together as a single app bundle to share or submit to the Mac App Store. You can test this at any time by selecting “Any Mac” as the target in the toolbar.

Test multiple architectures.

On the new Mac with Apple Silicon, you can run and debug apps running on either the native architecture or on Intel virtualization by selecting “My Mac (Rosetta)” in the toolbar.

Multiplatform template

New multiplatform app templates set up new projects to easily share code among iOS, iPadOS, and macOS using SwiftUI and the new lifecycle APIs. The project structure encourages sharing code across all platforms, while creating special custom experiences for each platform where it makes sense for your app.

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New tools in Xcode let you create StoreKit files that describe the various subscription and in-app purchase products your app can offer, and create test scenarios to make sure everything works great for your customers — all locally testable on your Mac.

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Download Xcode 12 and use these resources to build apps for all Apple platforms.