http://dl.gi.de/handle/20.500.12116/1911 2026-07-23T09:11:05Z 2026-07-23T09:11:05Z Nowak, Fabian Bromberger, Michael Karl, Wolfgang http://dl.gi.de/handle/20.500.12116/1951 2018-09-22T08:26:12Z 2014-01-01T00:00:00Z

An Architecture Framework for Porting Applications to FPGAs Nowak, Fabian; Bromberger, Michael; Karl, Wolfgang High-level language converters help creating FPGAbased accelerators and allow to rapidly come up with a working prototype. But the generated state machines do often not perform as optimal as hand-designed control units, and they require much area. Also, the created deep pipelines are not very efficient for small amounts of data. Our approach is an architecture framework of hand-coded building blocks (BBs). A microprogrammable control unit allows programming the BBs to perform computations in a data-flow style. We accelerate applications further by executing independent tasks in parallel on different BBs. Our microprogram implementation for the Conjugate-Gradient method on our data-driven, microprogrammable, task-parallel architecture framework on the Convey HC-1 is competitive with a 24-thread Intel Westmere system. It is 1.2× faster using only one out of four available FPGAs, thereby proving its potential for accelerating numerical applications. Moreover, we show that hardware developers can change the BBs and thereby reduce iteration count of a numerical algorithm like the ConjugateGradient method to less than 0.5× due to more precise operations inside the BBs, speeding up execution time 2.47×.

2014-01-01T00:00:00Z Flehmig, Martin Feldhoff, Kim Markwardt, Ulf http://dl.gi.de/handle/20.500.12116/1948 2018-09-22T08:26:12Z 2014-01-01T00:00:00Z

ScaFES: An Open-Source Framework for Explicit Solvers Combining High-Scalability with User-Friendliness Flehmig, Martin; Feldhoff, Kim; Markwardt, Ulf We present ScaFES, an open-source HPC framework written in C++11 for solving initial boundary value problems using explicit numerical methods in time on structured grids. It is designed to be highly-scalable and very user-friendly, i.e. to exploit all levels of parallelism and provide easy-to-use interfaces. Besides, the numerical nomenclature is reflected in a nearly oneto-one mapping. We describe how the framework works internally by presenting the core components of ScaFES, which modern C++ technologies are used, which parallelization methods are employed, and how the communication can be hidden behind during the update phase of a time step. Finally, we show how a multidimensional heat equation problem discretized via the finite difference method in space and via the explicit Euler scheme in time can be implemented and solved using ScaFES in about 60 lines. In order to demonstrate the excellent performance of ScaFES, we compare ScaFES to PETSc on the basis of the implemented heat equation example in two dimensions and present scalability results w.r.t. MPI and OpenMP achieved on HPC clusters at the ZIH.

2014-01-01T00:00:00Z Sobe, Peter Schumann, Peter http://dl.gi.de/handle/20.500.12116/1949 2018-09-22T08:26:12Z 2014-01-01T00:00:00Z

A Perfomance Study of Parallel Cauchy Reed/Solomon Coding Sobe, Peter; Schumann, Peter Cauchy-Reed/Solomon coding is applied to tolerate failures of memories and data storage devices in computer systems. In order to obtain a high data access bandwidth, the calculations for coding must be fast and it is required to utilize parallelism. For a software-based system, the most promising approach is data parallelism which can be easily implemented with OpenMP on a multicore or multiprocessor computer. A beneficial aspect is the clear mathematical nature of coding operations that supports functional parallelism as well. We report on a storage system application that generates the encoder and decoder as C-code automatically from a parametric description of the system and inserts OpenMP directives in the code automatically. We compare the performance in terms of achieved data throughput for data parallelism and for functional parallelism that is generated using OpenMP.

2014-01-01T00:00:00Z Christgau, Steffen Spazier, Johannes Schnor, Bettina Hammitzsch, Martin Babeyko, Andrey Wächter, Joachim http://dl.gi.de/handle/20.500.12116/1950 2018-09-22T08:26:12Z 2014-01-01T00:00:00Z

A comparison of CUDA and OpenACC: Accelerating the Tsunami Simulation EasyWave Christgau, Steffen; Spazier, Johannes; Schnor, Bettina; Hammitzsch, Martin; Babeyko, Andrey; Wächter, Joachim This paper presents an GPU accelerated version of the tsunami simulation EasyWave. Using two different GPU generations (Nvidia Tesla and Fermi) different optimization techniques were applied to the application following the principle of locality. Their performance impact was analyzed for both hardware generations. The Fermi GPU not only has more cores, but also possesses a L2 cache shared by all streaming multiprocessors. It is revealed that even the most tuned code on the Tesla does not reach the performance of the unoptimized code on the Fermi GPU. Further, a comparison between CUDA and OpenACC shows that the platform independent approach does not reach the speed of the native CUDA code. A deeper analysis shows that memory access patterns have a critical impact on the compute kernels’ performance, although this seems to be caused by the compiler in use.

2014-01-01T00:00:00Z