TY - GEN A1 - Noack, Matthias A1 - Wende, Florian A1 - Zitzlsberger, Georg A1 - Klemm, Michael A1 - Steinke, Thomas T1 - KART – A Runtime Compilation Library for Improving HPC Application Performance N2 - 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. T3 - ZIB-Report - 16-48 Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-60730 SN - 1438-0064 ER - TY - CHAP A1 - Noack, Matthias A1 - Wende, Florian A1 - Steinke, Thomas A1 - Cordes, Frank T1 - A Unified Programming Model for Intra- and Inter-Node Offloading on Xeon Phi Clusters T2 - SC '14: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. SC14, November 16-21, 2014, New Orleans, Louisiana, USA N2 - Standard offload programming models for the Xeon Phi, e.g. Intel LEO and OpenMP 4.0, are restricted to a single compute node and hence a limited number of coprocessors. Scaling applications across a Xeon Phi cluster/supercomputer thus requires hybrid programming approaches, usually MPI+X. In this work, we present a framework based on heterogeneous active messages (HAM-Offload) that provides the means to offload work to local and remote (co)processors using a unified offload API. Since HAM-Offload provides similar primitives as current local offload frameworks, existing applications can be easily ported to overcome the single-node limitation while keeping the convenient offload programming model. We demonstrate the effectiveness of the framework by using it to enable a real-world application from the field of molecular dynamics to use multiple local and remote Xeon Phis. The evaluation shows good scaling behavior. Compared with LEO, performance is equal for large offloads and significantly better for small offloads. Y1 - 2014 UR - http://dl.acm.org/citation.cfm?id=2683616 U6 - https://doi.org/10.1109/SC.2014.22 ER - TY - CHAP A1 - Noack, Matthias A1 - Wende, Florian A1 - Zitzlsberger, Georg A1 - Klemm, Michael A1 - Steinke, Thomas T1 - KART - A Runtime Compilation Library for Improving HPC Application Performance T2 - 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 N2 - 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. Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-67630-2_29 N1 - Best Paper Award VL - 10524 SP - 389 EP - 403 PB - Springer International Publishing ER - TY - CHAP A1 - Wende, Florian A1 - Noack, Matthias A1 - Steinke, Thomas A1 - Klemm, Michael A1 - Zitzlsberger, Georg A1 - Newburn, Chris J. ED - Dutot, Pierre-Francois ED - Trystram, Denis T1 - Portable SIMD Performance with OpenMP* 4.x Compiler Directives N2 - 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. Y1 - 2016 SN - 978-3-319-43659-3 U6 - https://doi.org/10.1007/978-3-319-43659-3_20 VL - Euro-Par 2016: Parallel Processing: 22nd International Conference on Parallel and Distributed Computing PB - Springer International Publishing ER - TY - CHAP A1 - Wende, Florian A1 - Noack, Matthias A1 - Schütt, Thorsten A1 - Sachs, Stephen A1 - Steinke, Thomas T1 - Application Performance on a Cray XC30 Evaluation System with Xeon Phi Coprocessors at HLRN-III T2 - Cray User Group Y1 - 2015 ER - TY - CHAP A1 - Noack, Matthias A1 - Wende, Florian A1 - Oertel, Klaus-Dieter ED - Reinders, James ED - Jeffers, Jim T1 - OpenCL: There and Back Again T2 - High Performance Parallelism Pearls Y1 - 2015 SN - 978-0-12-803819-2 VL - 2 SP - 355 EP - 378 PB - Morgan Kaufman, Elsevier ER - TY - JOUR A1 - Knoop, Helge A1 - Gronemeier, Tobias A1 - Sühring, Matthias A1 - Steinbach, Peter A1 - Noack, Matthias A1 - Wende, Florian A1 - Steinke, Thomas A1 - Knigge, Christoph A1 - Raasch, Siegfried A1 - Ketelsen, Klaus T1 - Porting the MPI-parallelized LES model PALM to multi-GPU systems and many integrated core processors: an experience report JF - International Journal of Computational Science and Engineering. Special Issue on: Novel Strategies for Programming Accelerators N2 - 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. Y1 - 2017 PB - Inderscience ET - Special Issue on: Novel Strategies for Programming Accelerators ER -