PGI Rolls Out Support for Volta 100 in its 2017 Compilers and Tools Suite

By John Russell

September 14, 2017

PGI today announced a fairly lengthy list of new features to version 17.7 of its 2017 Compilers and Tools. The centerpiece of the additions is support for the Tesla Volta 100 GPU, Nvidia’s newest flagship silicon announced in April and now shipping to customers.

The Volta V100, developed at a cost of $3 billion, is a giant chip, 33 percent larger than the Pascal P100 and once again “the biggest GPU ever made.” Fabricated by TSMC on a custom 12-nm FFN high performance manufacturing process, the V100 GPU squeezes 21.1 billion transistors and almost 100 billion via connectors on an 815 mm2 die, about the size of the Apple watch,  (See HPCwire articles, Nvidia’s Mammoth Volta GPU Aims High for AI, HPC and First Volta-based Nvidia DGX Systems Ship to Boston-based Healthcare Providers)

Overall, says PGI, the new features in version 17.7 will help deliver improved performance and programming simplicity to high-performance computing (HPC) developers who target multicore CPUs and heterogeneous GPU-accelerated systems.

“We’re seeing a 1.5-2x performance improvement in OpenACC programs compiled with PGI 17.7 on Volta compared to Pascal,” said Michael Wolfe of Nvidia’s PGI compilers & tools group. “The support in PGI 17.7 for OpenACC with CUDA Unified Memory simplifies initial porting of applications to GPUs, the improved data handling for C++14 lambdas in OpenACC is really important to many C++ programmers, and the PGI Unified Binary for OpenACC to target both multicore CPUs and GPUs is a great new feature for ISVs that need to deliver a single GPU-accelerated binary to all of their customers.”

In this latest release, PGI OpenACC and CUDA Fortran now support Volta GV100 GPU, “offering more memory bandwidth, more streaming multiprocessors, next-generation Nvidia NVLink and new microarchitectural features that add up to better performance and programmability” according to PGI which is owned by Nvidia.

PGI 17.7 compilers also now leverage CUDA Unified Memory to simplify OpenACC programming on GPU-accelerated systems. When OpenACC allocatable data is placed in CUDA Unified Memory using a simple compiler option, no explicit data movement code or directives are needed.

Other key new features of the PGI 17.7 Compilers & Tools include:

  • OpenMP 4.5 for Multicore CPUs– Initial support for OpenMP 4.5 syntax and features allows the compilation of most OpenMP 4.5 programs for parallel execution across all the cores of a multicore CPU system. TARGET regions are implemented with default support for the multicore host as the target, and PARALLEL and DISTRIBUTE loops are parallelized across all OpenMP threads.
  • Automatic Deep Copy of Fortran Derived Types– Movement of aggregate, or deeply nested Fortran data objects between CPU host and GPU device memory, including traversal and management of pointer-based objects, is now supported using OpenACC directives.
  • C++ Enhancements– The PGI 17.7 C++ compiler includes incremental C++17 features, and is supported as a CUDA 9.0 NVCC host compiler. It delivers an average 20 percent performance improvement on the LCALS loops benchmarks.
  • Use C++14 Lambdas with Capture in OpenACC Regions–  C++ lambda expressions provide a convenient way to define anonymous function objects at the location where they are invoked or passed as arguments. Starting with the PGI 17.7 release, lambdas are supported in OpenACC compute regions in C++ programs, for example to drive code generation customized to different programming models or platforms.  C++14 opens doors for more lambda use cases, especially for polymorphic lambdas. Those capabilities are now usable in OpenACC programs.
  • Interoperability with the cuSOLVER Library– call optimized cuSolverDN routines from CUDA Fortran and OpenACC Fortran, C and C++ using the PGI-supplied interface module and the PGI-compiled version of the cuSOLVER library bundled with PGI 17.7.
  • PGI Unified Binary for NVIDIA Tesla and Multicore CPUs– use OpenACC to build applications for both GPU acceleration and parallel execution on multicore CPUs. When run on a GPU-enabled system, OpenACC regions offload and execute on the GPU. When run on a system without GPUs installed, OpenACC regions execute in parallel across all CPU cores in the system.
  • New Profiling features for CUDA Unified Memory and OpenACC– The PGI 17.7 Profiler adds new OpenACC profiling features including support on multicore CPUs with or without attached GPUs, and a new summary view that shows time spent in each OpenACC construct. New CUDA Unified Memory features include correlating CPU page faults with the source code lines where the associated data was allocated, support for new CUDA Unified Memory page thrashing, throttling and remote map events, NVLink support and more.

Other features and enhancements of PGI 17.7 include comprehensive support for environment modules on all supported platforms, prebuilt versions of popular open source libraries and applications, and new “Introduction to Parallel Computing with OpenACC” video tutorial series. PGI 17.7 is available for download today from the PGI website to all PGI Professional customers with active maintenance.

PGI includes high-performance parallel Fortran, C and C++ compilers and tools for x86-64 and OpenPOWER CPU processor-based systems and NVIDIA Tesla GPU Accelerators running Linux, Microsoft Windows or Apple macOS operating systems.

Link to complete list of PGI 17.7 features: http://www.pgicompilers.com/products/new-in-pgi.htm

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

ARM, Fujitsu Targeting Open-source Software for Power Efficiency in 2-nm Chip

July 19, 2024

Fujitsu and ARM are relying on open-source software to bring power efficiency to an air-cooled supercomputing chip that will ship in 2027. Monaka chip, which will be made using the 2-nanometer process, is based on the Read more…

SCALEing the CUDA Castle

July 18, 2024

In a previous article, HPCwire has reported on a way in which AMD can get across the CUDA moat that protects the Nvidia CUDA castle (at least for PyTorch AI projects.). Other tools have joined the CUDA castle siege. AMD Read more…

Quantum Watchers – Terrific Interview with Caltech’s John Preskill by CERN

July 17, 2024

In case you missed it, there's a fascinating interview with John Preskill, the prominent Caltech physicist and pioneering quantum computing researcher that was recently posted by CERN’s department of experimental physi Read more…

Aurora AI-Driven Atmosphere Model is 5,000x Faster Than Traditional Systems

July 16, 2024

While the onset of human-driven climate change brings with it many horrors, the increase in the frequency and strength of storms poses an enormous threat to communities across the globe. As climate change is warming ocea Read more…

Researchers Say Memory Bandwidth and NVLink Speeds in Hopper Not So Simple

July 15, 2024

Researchers measured the real-world bandwidth of Nvidia's Grace Hopper superchip, with the chip-to-chip interconnect results falling well short of theoretical claims. A paper published on July 10 by researchers in the U. Read more…

Belt-Tightening in Store for Most Federal FY25 Science Budets

July 15, 2024

If it’s summer, it’s federal budgeting time, not to mention an election year as well. There’s an excellent summary of the curent state of FY25 efforts reported in AIP’s policy FYI: Science Policy News. Belt-tight Read more…

SCALEing the CUDA Castle

July 18, 2024

In a previous article, HPCwire has reported on a way in which AMD can get across the CUDA moat that protects the Nvidia CUDA castle (at least for PyTorch AI pro Read more…

Aurora AI-Driven Atmosphere Model is 5,000x Faster Than Traditional Systems

July 16, 2024

While the onset of human-driven climate change brings with it many horrors, the increase in the frequency and strength of storms poses an enormous threat to com Read more…

Shutterstock 1886124835

Researchers Say Memory Bandwidth and NVLink Speeds in Hopper Not So Simple

July 15, 2024

Researchers measured the real-world bandwidth of Nvidia's Grace Hopper superchip, with the chip-to-chip interconnect results falling well short of theoretical c Read more…

Shutterstock 2203611339

NSF Issues Next Solicitation and More Detail on National Quantum Virtual Laboratory

July 10, 2024

After percolating for roughly a year, NSF has issued the next solicitation for the National Quantum Virtual Lab program — this one focused on design and imple Read more…

NCSA’s SEAS Team Keeps APACE of AlphaFold2

July 9, 2024

High-performance computing (HPC) can often be challenging for researchers to use because it requires expertise in working with large datasets, scaling the softw Read more…

Anders Jensen on Europe’s Plan for AI-optimized Supercomputers, Welcoming the UK, and More

July 8, 2024

The recent ISC24 conference in Hamburg showcased LUMI and other leadership-class supercomputers co-funded by the EuroHPC Joint Undertaking (JU), including three Read more…

Generative AI to Account for 1.5% of World’s Power Consumption by 2029

July 8, 2024

Generative AI will take on a larger chunk of the world's power consumption to keep up with the hefty hardware requirements to run applications. "AI chips repres Read more…

US Senators Propose $32 Billion in Annual AI Spending, but Critics Remain Unconvinced

July 5, 2024

Senate leader, Chuck Schumer, and three colleagues want the US government to spend at least $32 billion annually by 2026 for non-defense related AI systems.  T Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Everyone Except Nvidia Forms Ultra Accelerator Link (UALink) Consortium

May 30, 2024

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock_1687123447

Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs

June 30, 2024

Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst fir Read more…

AMD Clears Up Messy GPU Roadmap, Upgrades Chips Annually

June 3, 2024

In the world of AI, there's a desperate search for an alternative to Nvidia's GPUs, and AMD is stepping up to the plate. AMD detailed its updated GPU roadmap, w Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Intel’s Next-gen Falcon Shores Coming Out in Late 2025 

April 30, 2024

It's a long wait for customers hanging on for Intel's next-generation GPU, Falcon Shores, which will be released in late 2025.  "Then we have a rich, a very Read more…

Leading Solution Providers

Contributors

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

IonQ Plots Path to Commercial (Quantum) Advantage

July 2, 2024

IonQ, the trapped ion quantum computing specialist, delivered a progress report last week firming up 2024/25 product goals and reviewing its technology roadmap. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire