@misc{WendeSteinke2013, author = {Wende, Florian and Steinke, Thomas}, title = {Swendsen-Wang Multi-Cluster Algorithm for the 2D/3D Ising Model on Xeon Phi and GPU}, issn = {1438-0064}, doi = {10.1145/2503210.2503254}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42187}, year = {2013}, abstract = {Simulations of the critical Ising model by means of local update algorithms suffer from critical slowing down. One way to partially compensate for the influence of this phenomenon on the runtime of simulations is using increasingly faster and parallel computer hardware. Another approach is using algorithms that do not suffer from critical slowing down, such as cluster algorithms. This paper reports on the Swendsen-Wang multi-cluster algorithm on Intel Xeon Phi coprocessor 5110P, Nvidia Tesla M2090 GPU, and x86 multi-core CPU. We present shared memory versions of the said algorithm for the simulation of the two- and three-dimensional Ising model. We use a combination of local cluster search and global label reduction by means of atomic hardware primitives. Further, we describe an MPI version of the algorithm on Xeon Phi and CPU, respectively. Significant performance improvements over known im plementations of the Swendsen-Wang algorithm are demonstrated.}, language = {en} } @article{WendeMarsmanKimetal.2018, author = {Wende, Florian and Marsman, Martijn and Kim, Jeongnim and Vasilev, Fedor and Zhao, Zhengji and Steinke, Thomas}, title = {OpenMP in VASP: Threading and SIMD}, journal = {International Journal of Quantum Chemistry}, number = {Emerging Architectures in Computational Chemistry}, publisher = {Wiley Online Library}, doi = {10.1002/qua.25851}, pages = {e25851}, year = {2018}, abstract = {The Vienna Ab initio Simulation Package (VASP) is a widely used electronic structure code that originally exploits process-level parallelism through the Message Passing Interface (MPI) for work distribution within and across nodes. Architectural changes of modern parallel processors urge programmers to address thread- and data-level parallelism as well to benefit most from the available compute resources within a node. We describe for VASP how to approach for an MPI + OpenMP parallelization including data-level parallelism through OpenMP SIMD constructs together with a generic high-level vector coding scheme. We can demonstrate an improved scalability of VASP and more than 20\% gain over the MPI-only version, as well as a 2x increased performance of collective operations using the multiple-endpoint MPI feature. The high-level vector coding scheme applied to VASP's general gradient approximation routine gives up 9x performance gain on AVX512 platforms with the Intel compiler.}, language = {en} } @inproceedings{WendeCordesSteinke2012, author = {Wende, Florian and Cordes, Frank and Steinke, Thomas}, title = {On Improving the Performance of Multi-threaded CUDA Applications with Concurrent Kernel Execution by Kernel Reordering}, booktitle = {Application Accelerators in High Performance Computing (SAAHPC), 2012 Symposium on}, doi = {10.1109/SAAHPC.2012.12}, pages = {74 -- 83}, year = {2012}, language = {en} } @misc{NoackWendeZitzlsbergeretal.2016, author = {Noack, Matthias and Wende, Florian and Zitzlsberger, Georg and Klemm, Michael and Steinke, Thomas}, title = {KART - A Runtime Compilation Library for Improving HPC Application Performance}, issn = {1438-0064}, doi = {10.1007/978-3-319-67630-2_29}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-60730}, year = {2016}, abstract = {The effectiveness of ahead-of-time compiler optimization heavily depends on the amount of available information at compile time. Input-specific information that is only available at runtime cannot be used, although it often determines loop counts, branching predicates and paths, as well as memory-access patterns. It can also be crucial for generating efficient SIMD-vectorized code. This is especially relevant for the many-core architectures paving the way to exascale computing, which are more sensitive to code-optimization. We explore the design-space for using input-specific information at compile-time and present KART, a C++ library solution that allows developers to compile, link, and execute code (e.g., C, C++ , Fortran) at application runtime. Besides mere runtime compilation of performance-critical code, KART can be used to instantiate the same code multiple times using different inputs, compilers, and options. Other techniques like auto-tuning and code-generation can be integrated into a KART-enabled application instead of being scripted around it. We evaluate runtimes and compilation costs for different synthetic kernels, and show the effectiveness for two real-world applications, HEOM and a WSM6 proxy.}, language = {en} } @inproceedings{WendeNoackSteinkeetal.2016, author = {Wende, Florian and Noack, Matthias and Steinke, Thomas and Klemm, Michael and Zitzlsberger, Georg and Newburn, Chris J.}, title = {Portable SIMD Performance with OpenMP* 4.x Compiler Directives}, volume = {Euro-Par 2016: Parallel Processing: 22nd International Conference on Parallel and Distributed Computing}, editor = {Dutot, Pierre-Francois and Trystram, Denis}, publisher = {Springer International Publishing}, isbn = {978-3-319-43659-3}, doi = {10.1007/978-3-319-43659-3_20}, year = {2016}, abstract = {Effective vectorization is becoming increasingly important for high performance and energy efficiency on processors with wide SIMD units. Compilers often require programmers to identify opportunities for vectorization, using directives to disprove data dependences. The OpenMP 4.x SIMD directives strive to provide portability. We investigate the ability of current compilers (GNU, Clang, and Intel) to generate SIMD code for microbenchmarks that cover common patterns in scientific codes and for two kernels from the VASP and the MOM5/ERGOM application. We explore coding strategies for improving SIMD performance across different compilers and platforms (Intel® Xeon® processor and Intel® Xeon Phi™ (co)processor). We compare OpenMP* 4.x SIMD vectorization with and without vector data types against SIMD intrinsics and C++ SIMD types. Our experiments show that in many cases portable performance can be achieved. All microbenchmarks are available as open source as a reference for programmers and compiler experts to enhance SIMD code generation.}, language = {en} } @inproceedings{WendeMarsmanSteinke2016, author = {Wende, Florian and Marsman, Martijn and Steinke, Thomas}, title = {On Enhancing 3D-FFT Performance in VASP}, booktitle = {CUG Proceedings}, year = {2016}, language = {en} } @article{AlhaddadFoerstnerGrothetal.2021, author = {Alhaddad, Samer and F{\"o}rstner, Jens and Groth, Stefan and Gr{\"u}newald, Daniel and Grynko, Yevgen and Hannig, Frank and Kenter, Tobias and Pfreundt, Franz-Josef and Plessl, Christian and Schotte, Merlind and Steinke, Thomas and Teich, J{\"u}rgen and Weiser, Martin and Wende, Florian}, title = {HighPerMeshes - A Domain-Specific Language for Numerical Algorithms on Unstructured Grids}, journal = {Euro-Par 2020: Parallel Processing Workshops.}, publisher = {Springer}, doi = {10.1007/978-3-030-71593-9_15}, pages = {185 -- 196}, year = {2021}, abstract = {Solving partial differential equations on unstructured grids is a cornerstone of engineering and scientific computing. Nowadays, heterogeneous parallel platforms with CPUs, GPUs, and FPGAs enable energy-efficient and computationally demanding simulations. We developed the HighPerMeshes C++-embedded Domain-Specific Language (DSL) for bridging the abstraction gap between the mathematical and algorithmic formulation of mesh-based algorithms for PDE problems on the one hand and an increasing number of heterogeneous platforms with their different parallel programming and runtime models on the other hand. Thus, the HighPerMeshes DSL aims at higher productivity in the code development process for multiple target platforms. We introduce the concepts as well as the basic structure of the HighPer-Meshes DSL, and demonstrate its usage with three examples, a Poisson and monodomain problem, respectively, solved by the continuous finite element method, and the discontinuous Galerkin method for Maxwell's equation. The mapping of the abstract algorithmic description onto parallel hardware, including distributed memory compute clusters is presented. Finally, the achievable performance and scalability are demonstrated for a typical example problem on a multi-core CPU cluster.}, language = {en} } @article{KnoopGronemeierSuehringetal.2017, author = {Knoop, Helge and Gronemeier, Tobias and S{\"u}hring, Matthias and Steinbach, Peter and Noack, Matthias and Wende, Florian and Steinke, Thomas and Knigge, Christoph and Raasch, Siegfried and Ketelsen, Klaus}, title = {Porting the MPI-parallelized LES model PALM to multi-GPU systems and many integrated core processors: an experience report}, journal = {International Journal of Computational Science and Engineering. Special Issue on: Novel Strategies for Programming Accelerators}, edition = {Special Issue on: Novel Strategies for Programming Accelerators}, publisher = {Inderscience}, year = {2017}, abstract = {The computational power and availability of graphics processing units (GPUs), such as the Nvidia Tesla, and Many Integrated Core (MIC) processors, such as the Intel Xeon Phi, on high performance computing (HPC) systems is rapidly evolving. However, HPC applications need to be ported to take advantage of such hardware. This paper is a report on our experience of porting the MPI+OpenMP parallelised large-eddy simulation model (PALM) to multi-GPU as well as to MIC processor environments using the directive-based high level programming paradigm OpenACC and OpenMP, respectively. PALM is a Fortran-based computational fluid dynamics software package, used for the simulation of atmospheric and oceanic boundary layers to answer questions linked to fundamental atmospheric turbulence research, urban modelling, aircraft safety and cloud physics. Development of PALM started in 1997, the project currently entails 140 kLOC and is used on HPC farms of up to 43,200 cores. The main challenges we faced during the porting process are the size and complexity of the PALM code base, its inconsistent modularisation and the complete lack of a unit-test suite. We report the methods used to identify performance issues as well as our experiences with state-of-the-art profiling tools. Moreover, we outline the required porting steps in order to properly execute our code on GPUs and MIC processors, describe the problems and bottlenecks that we encountered during the porting process, and present separate performance tests for both architectures. These performance tests, however, do not provide any benchmark information that compares the performance of the ported code between the two architectures.}, language = {en} } @incollection{NoackWendeZitzlsbergeretal.2017, author = {Noack, Matthias and Wende, Florian and Zitzlsberger, Georg and Klemm, Michael and Steinke, Thomas}, title = {KART - A Runtime Compilation Library for Improving HPC Application Performance}, volume = {10524}, booktitle = {High Performance Computing: ISC High Performance 2017 International Workshops, DRBSD, ExaComm, HCPM, HPC-IODC, IWOPH, IXPUG, P^3MA, VHPC, Visualization at Scale, WOPSSS, Frankfurt, Germany, June 18-22, 2017, Revised Selected Papers}, publisher = {Springer International Publishing}, doi = {10.1007/978-3-319-67630-2_29}, pages = {389 -- 403}, year = {2017}, abstract = {The effectiveness of ahead-of-time compiler optimization heavily depends on the amount of available information at compile time. Input-specific information that is only available at runtime cannot be used, although it often determines loop counts, branching predicates and paths, as well as memory-access patterns. It can also be crucial for generating efficient SIMD-vectorized code. This is especially relevant for the many-core architectures paving the way to exascale computing, which are more sensitive to code-optimization. We explore the design-space for using input-specific information at compile-time and present KART, a C++ library solution that allows developers tocompile, link, and execute code (e.g., C, C++ , Fortran) at application runtime. Besides mere runtime compilation of performance-critical code, KART can be used to instantiate the same code multiple times using different inputs, compilers, and options. Other techniques like auto-tuning and code-generation can be integrated into a KART-enabled application instead of being scripted around it. We evaluate runtimes and compilation costs for different synthetic kernels, and show the effectiveness for two real-world applications, HEOM and a WSM6 proxy.}, language = {en} } @inproceedings{WendeNoackSchuettetal.2015, author = {Wende, Florian and Noack, Matthias and Sch{\"u}tt, Thorsten and Sachs, Stephen and Steinke, Thomas}, title = {Application Performance on a Cray XC30 Evaluation System with Xeon Phi Coprocessors at HLRN-III}, booktitle = {Cray User Group}, year = {2015}, language = {en} }