If you use standard language parallelism, it may even be possible without any code changes at all. ") nYYoEP0Q) c /L mQ #-s2g93*U 0000003565 00000 n The foundation of the NVIDIA strategy is providing a rich, mature set of SDKs and libraries on which applications can be built. Instead, we expect that developers coming to the NVIDIA platform for the first time will use standard, parallel programming languages, such as ISO C++, ISO Fortran, and Python. /Title (Methods and tools of parallel programming) Performance Fortran / Fortran 90D Compiler at Syracuse, Interprocessor
The result is repeated code and the introduction of an additional API, OpenMP, into the source. 0000004323 00000 n We worked with the developers to rewrite their existing OpenMP-based code to use C++ Parallel Algorithms. On top of this, NVIDIA layers the three different programming approaches: Each of these approaches makes tradeoffs in terms of performance, productivity, and code portability. For GPUs, there are versions available using OpenACC, OpenMP target offloading, and now Fortran do concurrent loops. stream
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There is an incredibly rich literature on languages for parallel computing, thus it is difficult for researchers and practitioners, even experienced in this very field, to get a grasp on them. endobj 0000025681 00000 n 0000014575 00000 n Professor Jonas Latt discussed this application in several GTC sessions, showing how code written in ISO C++ without any external SDK dependencies can run with multiple compilers and on multiple hardware platforms, including NVIDIA GPUs.
0000030721 00000 n Copyright 2022 ACM, Inc. We use cookies to ensure that we give you the best experience on our website. ph4 3UENJ| 0000040743 00000 n The code on the right is the same routine, but rewritten using the C++ transform_reduce algorithm. Request permissions from [emailprotected]. Methods Library) v. 1.2a, Concurrent Systems Architecture 0000041620 00000 n In summary, using standard language parallelism has the following benefits: Here are several talks from GTC21 that can provide you with even more detail about this approach to parallel programming: For more information, see the following resources: Over 500 GTC sessions now available free on NVIDIA On-Demand, Build Tools for the 3D World with the Extend the Omniverse Contest, Designing Arithmetic Circuits with Deep Reinforcement Learning, Building Generally Capable AI Agents with MineDojo, The Full Stack Optimization Powering NVIDIA MLPerf Training v2.0 Performance, Dealing with Outliers Using Three Robust Linear Regression Models, Optimizing and Serving Models with NVIDIA TensorRT and NVIDIA Triton, Running Multiple Applications on the Same Edge Devices, Introducing QODA: The Platform for Hybrid Quantum-Classical Computing, Adapting P-Tuning to Solve Non-English Downstream Tasks, Fluid Dynamics on GPUs with C++ Parallel Algorithms: State-of-the-Art Performance through a Hardware-Agnostic Approach, Porting a Scientific Application to GPU Using C++ Standard Parallelism, FortranCon2021: Standard Fortran on GPUs and its utility in quantum chemistry codes, NVIDIA Announces Availability for cuNumeric Public Alpha, Shifting through the Gears of GPU Programming: Understanding Performance and Portability Trade-offs, Accelerated Computing with Standard C++, Python, and Fortran, Standard language parallelism, which is the subject of this post, Languages for platform specialization, such as CUDA C++ and CUDA Fortran for obtaining the best possible performance on the NVIDIA platform, Compiler directives, bridging the gap between these two approaches by enabling incremental performance optimization, Full ISO language compliance, resulting in more portable code, Code that is more compact, easier to read, less error prone, Code that is parallel by default, so it can run without modification on more platforms, Learn more about the compiler support and other posts at. As they can all interoperate, you dont have to use a particular model but can mix any or all as desired.
Now that same code runs more than 13X faster by running on an NVIDIA A100 GPU. 0000004841 00000 n At the recent Workshop for Accelerator Programming Using Directives (WACCPD), collocated at the SC21 conference, a team of developers from Predictive Science Inc. showed their results in refactoring one of their production codes, which previously used OpenACC to run on NVIDIA GPUs, using do concurrent loops. %
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17 0 obj In this article, we report on planning, execution, and results of our systematic peer-reviewed as well as grey literature review, which aimed at providing such a snapshot by analysing 225 studies. Journal of Parallel and Distributed Computing.
For more information, see Fluid Dynamics on GPUs with C++ Parallel Algorithms: State-of-the-Art Performance through a Hardware-Agnostic Approach and Porting a Scientific Application to GPU Using C++ Standard Parallelism. It also removes the dependency on OpenMP, relying instead on the C++ standard template library, while maintaining a single source code for all platforms. 0/O. The ACM Digital Library is published by the Association for Computing Machinery. Theres a 13.5X performance improvement from the original code, running in parallel both on the CPU and GPU, using strictly ISO C++ code. 0000030312 00000 n
It is now commonly used in machine learning, data science, and even traditional modeling and simulation applications. 0000023601 00000 n 0000026500 00000 n /Length3 0 This paper received the award for best paper at the workshop, even though it required no directives at all for accelerator programming. Group (CSAG), Scalable Concurrent Programming Laboratory, Swiss Federal Institute of Technology This library allows data-parallel tasks to exchange distributed data structures using calls to simple communication functions. Copyright 2022 Elsevier B.V. or its licensors or contributors. 0000003304 00000 n For more information about cuNumeric, see NVIDIA Announces Availability for cuNumeric Public Alpha and watch the GTC On-Demand session, Legate: Scaling the Python Ecosystem. The code on the left uses OpenMP to parallelize the loops in the code across CPU threads.
The NumPy package is so prevalent in Python development that it is a near certainty that any HPC application written in Python uses it. 0000003744 00000 n Check if you have access through your login credentials or your institution to get full access on this article. 0000001491 00000 n Copyright 1997 Academic Press. The C++ programming language is consistently among the top programming languages in recent studies of programming trends. 0000015191 00000 n
In addition, results from two-dimensional FFT, convolution, and multiblock programs demonstrate that the HPF/MPI library can provide performance superior to that of pure HPF. 0000042367 00000 n Another example of an application using C++ Standard Parallelism is STLBM, a Lattice-Boltzmann solver from the University of Geneva. Just as with ISO C++, NVIDIA has been working with application developers to use standard language parallelism in Fortran to modernize their applications and make them parallel-first. If you start writing code using parallelism in standard programming languages, then you can come to the NVIDIA platform or any other platform with baseline code that is already capable of running in parallel. of Parallel Computing of University of Sherbrooke, JNNIE:The Joint Collective Communications Library (iCC), Templates Pure data-parallel languages such as High Performance Fortran version 1 (HPF) do not allow efficient expression of mixed task/data-parallel computations or the coupling of separately compiled data-parallel modules. HV P~3=.Z\4*Q9afsFXED1 Y4G6]bKU)5>Qw\~;Wa0*fwB8 0000040138 00000 n The Python language has had a meteoric rise in popularity over the past decade. >>
ScienceDirect is a registered trademark of Elsevier B.V. ScienceDirect is a registered trademark of Elsevier B.V. A Library-Based Approach to Task Parallelism in a Data-Parallel Language. 0000004012 00000 n
/Length 29213 - H !A2 KP A P Furthermore, this code could run in parallel on GPUs and multicore CPUs without modification.
/D (section.0.13) All rights reserved. na(k^6uV%4PWEYqmjZIR6b{HF%Ij3NGgx@8*, &E5Q %644.x!(6Gqeg1BxU By continuing you agree to the use of cookies. /Parent 20 0 R endobj 0000030614 00000 n We use cookies to help provide and enhance our service and tailor content and ads. 0000027284 00000 n 0000023369 00000 n `qRn (?[^_F`)@Wb2?|\y^yx_~ uc*| _ Z9 N0__t!/k2__Dn}Y;;z5?Z?_ey5w{w_+90sW+k Ej^krnY,C,wzN 0000004384 00000 n Institute for Computational and Applied Mathematics. Ive seen for several example applications that simply replacing references to NumPy in the code to instead refer to cuNumeric, I could weakly scale that application to the full size of the NVIDIA internal cluster, Selene, which is among the 10 fastest supercomputers in the world. 0000004507 00000 n Software-intensive systems in most domains, from autonomous vehicles to health, are becoming predominantly parallel to efficiently manage large amount of data in short (even real-) time. aUQGT3-{$GV/)VqfZq.*!2k_W N%DP#aQQQvD]P6I^$u~q)mP+7\+YDsdY)qoSHs4 U.3+r;SG5{zu>P=qv-`**W]U`;UF`utw2|z1ufqNz5]% Jv~[aD&rS /S /GoTo 0000040507 00000 n (EPFL)-Cray Parallel Application Technology Program, Center for Research on Parallel They compared the results of building this purely ISO Fortran application using NVIDIA nvfortran, gfortran, and ifort. With this work we provide a comprehensive, structured, and detailed snapshot of documented research on those languages to identify trends, technical characteristics, open challenges, and research directions. 0000026522 00000 n In his keynote address at GTC21 Fall, NVIDIA CEO Jensen Huang introduced the alpha release of cuNumeric, a library that is modeled after NumPy and which enables features similar to what I have discussed for ISO C++ and Fortran. To manage your alert preferences, click on the button below.
As it turns out, it is faster too! Jn?o.k 4t?X/ ptS5ws_=_{_:mk\AVvN[+n:`h&c RsUk1`v``rp/TY:.
NVIDIA is encouraging you to write applications parallel-first such that there is never a need to port applications to new platforms and standard language parallelism is the best approach to doing this, as it requires nothing more than the ISO standard languages. In this post, I highlight some successes in using this approach to parallel programming to demonstrate the most productive path to entering the NVIDIA CUDA ecosystem. trailer << /Size 363 /Info 304 0 R /Root 307 0 R /Prev 371863 /ID[<9256a8784bb3bf3be809652dfbb48622>] >> startxref 0 %%EOF 307 0 obj << /Type /Catalog /Pages 300 0 R /Metadata 305 0 R /Names 309 0 R /ViewerPreferences << /FitWindow true >> /Outlines 311 0 R /PageMode /UseOutlines /OpenAction 308 0 R >> endobj 308 0 obj << /S /GoTo /D [ 310 0 R /Fit ] >> endobj 309 0 obj << /Dests 298 0 R >> endobj 361 0 obj << /S 1643 /T 1925 /O 2011 /E 2027 /Filter /FlateDecode /Length 362 0 R >> stream 0000014965 00000 n They concluded that, for their application when using the nvfortran compiler, pure Fortran gave the performance that they required without the need for any directives. The resulting code is much more compact, making it less error prone, easier to read, and more maintainable. (~n (F(@ `*Y_o`x@ _{ Supplemental movie, appendix, image and software files for, A Comprehensive Exploration of Languages for Parallel Computing. f2-vzc 1^af[x;jm@jKQo4MmGY&:H~UKl_'[Ck@~re. >> NSF-NASA Initiative on Evaluation, Texas His application achieves more than a 12X performance improvement using GPUs. /A 19 0 R High 0000004135 00000 n 0000024820 00000 n
HUmle9F0D8=c.leu/+{`d$!~4L37d3&$Bj $d$*% }_~Ci*M%@:T1S{3NnnO/elZxk42j{}-Ojpd_BuA)$CBb]mvCM>ZHDYL8 FZ:T:cm The cuNumeric package, written on top of a package called Legate, enables NumPy applications to automatically scale their work not only onto GPUs but across GPUs in a large cluster. This code is fully ISO C++ compliant, capable of being built by any C++ compiler that supports C++17.
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Here are the results from a few of them. This is already an exciting achievement but to top that off, you can build this same code, changing only a compiler option to target an NVIDIA GPU instead of a multicore CPU. This alert has been successfully added and will be sent to: You will be notified whenever a record that you have chosen has been cited.
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To maintain both a serial and parallel version of the code, the developers used #ifdef macros and compiler pragmas. 0000004567 00000 n We conclude that this synergistic combination of two parallel programming standards represents a useful approach to task parallelism in a data-parallel framework, increasing the range of problems addressable in HPF without requiring complex compiler technology. Figure 5 shows that the do concurrent loops perform at the same level as both OpenACC and OpenMP target offloading on NVIDIA GPUs but without the need to include these additional APIs in the application. Xyw!:{XA-g9H$BJ,{$iIdUvo04e gap,A'"@!*7aEPp** {`M9&KY83|zmr^/y^9cH#Dg D63-=t6a 0000041598 00000 n What is notable is that his baseline for comparison is a source code that is parallel by default, using the parallel algorithms in the C++17 standard template library to express the parallelism inherent in the application.
He categorized the experience of using ISO C++ to program for GPUs as a paradigm shift in cross-platform CPU/GPU programming. Rather than writing an application that is serial by default and then adding parallelism later, his team has written an application that is ready for any parallel platform on which they wish to run. On multicore CPUs, these tensor contractions use OpenMP for threading across CPU cores. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. 0000003952 00000 n 0000042389 00000 n Fortran began adding features to support parallel programming in Fortran 2008, enhanced these capabilities in Fortran 2018, and continues to refine them in the upcoming version, currently referred to as Fortran 202X. For NWChem, he isolated several performance-critical loops that perform tensor contractions and has written them using several programming models. 306 0 obj << /Linearized 1 /O 310 /H [ 1786 1518 ] /L 378113 /E 43095 /N 35 /T 371874 >> endobj xref 306 57 0000000016 00000 n
