@inproceedings{25, author = {{Lass, Michael and Kühne, Thomas and Plessl, Christian}}, booktitle = {{Workshop on Approximate Computing (AC)}}, title = {{{Using Approximate Computing in Scientific Codes}}}, year = {{2016}}, } @inproceedings{138, abstract = {{Hardware accelerators are becoming popular in academia and industry. To move one step further from the state-of-the-art multicore plus accelerator approaches, we present in this paper our innovative SAVEHSA architecture. It comprises of a heterogeneous hardware platform with three different high-end accelerators attached over PCIe (GPGPU, FPGA and Intel MIC). Such systems can process parallel workloads very efficiently whilst being more energy efficient than regular CPU systems. To leverage the heterogeneity, the workload has to be distributed among the computing units in a way that each unit is well-suited for the assigned task and executable code must be available. To tackle this problem we present two software components; the first can perform resource allocation at runtime while respecting system and application goals (in terms of throughput, energy, latency, etc.) and the second is able to analyze an application and generate executable code for an accelerator at runtime. We demonstrate the first proof-of-concept implementation of our framework on the heterogeneous platform, discuss different runtime policies and measure the introduced overheads.}}, author = {{Riebler, Heinrich and Vaz, Gavin Francis and Plessl, Christian and Trainiti, Ettore M. G. and Durelli, Gianluca C. and Del Sozzo, Emanuele and Santambrogio, Marco D. and Bolchini, Christina}}, booktitle = {{Proceedings of International Forum on Research and Technologies for Society and Industry (RTSI)}}, pages = {{1--5}}, publisher = {{IEEE}}, title = {{{Using Just-in-Time Code Generation for Transparent Resource Management in Heterogeneous Systems}}}, doi = {{10.1109/RTSI.2016.7740545}}, year = {{2016}}, } @inbook{156, abstract = {{Many modern compute nodes are heterogeneous multi-cores that integrate several CPU cores with fixed function or reconfigurable hardware cores. Such systems need to adapt task scheduling and mapping to optimise for performance and energy under varying workloads and, increasingly important, for thermal and fault management and are thus relevant targets for self-aware computing. In this chapter, we take up the generic reference architecture for designing self-aware and self-expressive computing systems and refine it for heterogeneous multi-cores. We present ReconOS, an architecture, programming model and execution environment for heterogeneous multi-cores, and show how the components of the reference architecture can be implemented on top of ReconOS. In particular, the unique feature of dynamic partial reconfiguration supports self-expression through starting and terminating reconfigurable hardware cores. We detail a case study that runs two applications on an architecture with one CPU and 12 reconfigurable hardware cores and present self-expression strategies for adapting under performance, temperature and even conflicting constraints. The case study demonstrates that the reference architecture as a model for self-aware computing is highly useful as it allows us to structure and simplify the design process, which will be essential for designing complex future compute nodes. Furthermore, ReconOS is used as a base technology for flexible protocol stacks in Chapter 10, an approach for self-aware computing at the networking level.}}, author = {{Agne, Andreas and Happe, Markus and Lösch, Achim and Plessl, Christian and Platzner, Marco}}, booktitle = {{Self-aware Computing Systems}}, pages = {{145--165}}, publisher = {{Springer International Publishing}}, title = {{{Self-aware Compute Nodes}}}, doi = {{10.1007/978-3-319-39675-0_8}}, year = {{2016}}, } @article{165, abstract = {{A broad spectrum of applications can be accelerated by offloading computation intensive parts to reconfigurable hardware. However, to achieve speedups, the number of loop it- erations (trip count) needs to be sufficiently large to amortize offloading overheads. Trip counts are frequently not known at compile time, but only at runtime just before entering a loop. Therefore, we propose to generate code for both the CPU and the coprocessor, and defer the offloading decision to the application runtime. We demonstrate how a toolflow, based on the LLVM compiler framework, can automatically embed dynamic offloading de- cisions into the application code. We perform in-depth static and dynamic analysis of pop- ular benchmarks, which confirm the general potential of such an approach. We also pro- pose to optimize the offloading process by decoupling the runtime decision from the loop execution (decision slack). The feasibility of our approach is demonstrated by a toolflow that automatically identifies suitable data-parallel loops and generates code for the FPGA coprocessor of a Convey HC-1. We evaluate the integrated toolflow with representative loops executed for different input data sizes.}}, author = {{Vaz, Gavin Francis and Riebler, Heinrich and Kenter, Tobias and Plessl, Christian}}, issn = {{0045-7906}}, journal = {{Computers and Electrical Engineering}}, pages = {{91--111}}, publisher = {{Elsevier}}, title = {{{Potential and Methods for Embedding Dynamic Offloading Decisions into Application Code}}}, doi = {{10.1016/j.compeleceng.2016.04.021}}, volume = {{55}}, year = {{2016}}, } @inproceedings{168, abstract = {{The use of heterogeneous computing resources, such as Graphic Processing Units or other specialized coprocessors, has become widespread in recent years because of their per- formance and energy efficiency advantages. Approaches for managing and scheduling tasks to heterogeneous resources are still subject to research. Although queuing systems have recently been extended to support accelerator resources, a general solution that manages heterogeneous resources at the operating system- level to exploit a global view of the system state is still missing.In this paper we present a user space scheduler that enables task scheduling and migration on heterogeneous processing resources in Linux. Using run queues for available resources we perform scheduling decisions based on the system state and on task characterization from earlier measurements. With a pro- gramming pattern that supports the integration of checkpoints into applications, we preempt tasks and migrate them between three very different compute resources. Considering static and dynamic workload scenarios, we show that this approach can gain up to 17% performance, on average 7%, by effectively avoiding idle resources. We demonstrate that a work-conserving strategy without migration is no suitable alternative.}}, author = {{Lösch, Achim and Beisel, Tobias and Kenter, Tobias and Plessl, Christian and Platzner, Marco}}, booktitle = {{Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)}}, pages = {{912--917}}, publisher = {{EDA Consortium / IEEE}}, title = {{{Performance-centric scheduling with task migration for a heterogeneous compute node in the data center}}}, year = {{2016}}, } @inproceedings{171, author = {{Kenter, Tobias and Vaz, Gavin Francis and Riebler, Heinrich and Plessl, Christian}}, booktitle = {{Workshop on Reconfigurable Computing (WRC)}}, title = {{{Opportunities for deferring application partitioning and accelerator synthesis to runtime (extended abstract)}}}, year = {{2016}}, } @article{1772, author = {{Torresen, Jim and Plessl, Christian and Yao, Xin}}, journal = {{IEEE Computer}}, keywords = {{self-awareness, self-expression}}, number = {{7}}, pages = {{18--20}}, publisher = {{IEEE Computer Society}}, title = {{{Self-Aware and Self-Expressive Systems – Guest Editor's Introduction}}}, doi = {{10.1109/MC.2015.205}}, volume = {{48}}, year = {{2015}}, } @misc{1794, abstract = {{Demands for computational power and energy efficiency of computing devices are steadily increasing. At the same time, following classic methods to increase speed and reduce energy consumption of these devices becomes increasingly difficult, bringing alternative methods into focus. One of these methods is approximate computing which utilizes the fact that small errors in computations are acceptable in many applications in order to allow acceleration of these computations or to increase energy efficiency. This thesis develops elements of a workflow that can be followed to apply approximate computing to existing applications. It proposes a novel heuristic approach to the localization of code paths that are suitable to approximate computing based on findings in recent research. Additionally, an approach to identification of approximable instructions within these code paths is proposed and used to implement simulation of approximation. The parts of the workflow are implemented with the goal to lay the foundation for a partly automated toolflow. Evaluation of the developed techniques shows that the proposed methods can help providing a convenient workflow, facilitating the first steps into the application of approximate computing.}}, author = {{Lass, Michael}}, publisher = {{Paderborn University}}, title = {{{Localization and Analysis of Code Paths Suitable for Acceleration using Approximate Computing}}}, year = {{2015}}, } @inproceedings{4465, abstract = {{The first year of studying has been extensively researched applying different theoretical lenses to better understand the transition into Higher Education (HE). It is of particular interest to investigate how students deal with frictions between themselves as individuals and what they perceive to be dominant features of the first-year culture of their studies. To tackle this question, a qualitative longitudinal study was conducted. Based on a sociocultural understanding of attitudes and motivations, its aim was to closely follow a relatively small but highly diverse sample of students throughout their first year at a business school in order to develop an in-depth understanding of each individual’s motivational and attitudinal development.}}, author = {{Jenert, Tobias and Brahm, Taiga}}, keywords = {{Enculturation, first-year students, beginning students, retention, drop-out}}, location = {{Chicago}}, title = {{{How Do They Find Their Place? A Longitudinal Study of Management Students' Attitudes and Motivations During Their First Year at Business School}}}, year = {{2015}}, } @misc{5413, author = {{Funke, Lukas}}, publisher = {{Universität Paderborn}}, title = {{{An LLVM Based Toolchain for Transparent Acceleration of Digital Image Processing Applications using FPGA Overlay Architectures}}}, year = {{2015}}, } @misc{5416, author = {{Löcke, Thomas}}, publisher = {{Universität Paderborn}}, title = {{{Instance-Specific Computing in Hard- and Software for Faster Solving of Complex Problems}}}, year = {{2015}}, } @misc{5419, author = {{Wallaschek, Felix}}, publisher = {{Universität Paderborn}}, title = {{{Accelerating Programmable Logic Controllers with the use of FPGAs}}}, year = {{2015}}, } @phdthesis{10624, abstract = {{The use of heterogeneous computing resources, such as graphics processing units or other specialized co-processors, has become widespread in recent years because of their performance and energy efficiency advantages. Operating system approaches that are limited to optimizing CPU usage are no longer sufficient for the efficient utilization of systems that comprise diverse resource types. Enabling task preemption on these architectures and migration of tasks between different resource types at run-time is not only key to improving the performance and energy consumption but also to enabling automatic scheduling methods for heterogeneous compute nodes. This thesis proposes novel techniques for run-time management of heterogeneous resources and enabling tasks to migrate between diverse hardware. It provides fundamental work towards future operating systems by discussing implications, limitations, and chances of the heterogeneity and introducing solutions for energy- and performance-efficient run-time systems. Scheduling methods to utilize heterogeneous systems by the use of a centralized scheduler are presented that show benefits over existing approaches in varying case studies.}}, author = {{Beisel, Tobias}}, isbn = {{978-3-8325-4155-2}}, pages = {{183}}, publisher = {{Logos Verlag Berlin GmbH}}, title = {{{Management and Scheduling of Accelerators for Heterogeneous High-Performance Computing}}}, year = {{2015}}, } @article{296, abstract = {{FPGAs are known to permit huge gains in performance and efficiency for suitable applications but still require reduced design efforts and shorter development cycles for wider adoption. In this work, we compare the resulting performance of two design concepts that in different ways promise such increased productivity. As common starting point, we employ a kernel-centric design approach, where computational hotspots in an application are identified and individually accelerated on FPGA. By means of a complex stereo matching application, we evaluate two fundamentally different design philosophies and approaches for implementing the required kernels on FPGAs. In the first implementation approach, we designed individually specialized data flow kernels in a spatial programming language for a Maxeler FPGA platform; in the alternative design approach, we target a vector coprocessor with large vector lengths, which is implemented as a form of programmable overlay on the application FPGAs of a Convey HC-1. We assess both approaches in terms of overall system performance, raw kernel performance, and performance relative to invested resources. After compensating for the effects of the underlying hardware platforms, the specialized dataflow kernels on the Maxeler platform are around 3x faster than kernels executing on the Convey vector coprocessor. In our concrete scenario, due to trade-offs between reconfiguration overheads and exposed parallelism, the advantage of specialized dataflow kernels is reduced to around 2.5x.}}, author = {{Kenter, Tobias and Schmitz, Henning and Plessl, Christian}}, journal = {{International Journal of Reconfigurable Computing (IJRC)}}, publisher = {{Hindawi}}, title = {{{Exploring Tradeoffs between Specialized Kernels and a Reusable Overlay in a Stereo-Matching Case Study}}}, doi = {{10.1155/2015/859425}}, volume = {{2015}}, year = {{2015}}, } @inproceedings{303, abstract = {{This paper introduces Binary Acceleration At Runtime(BAAR), an easy-to-use on-the-fly binary acceleration mechanismwhich aims to tackle the problem of enabling existentsoftware to automatically utilize accelerators at runtime. BAARis based on the LLVM Compiler Infrastructure and has aclient-server architecture. The client runs the program to beaccelerated in an environment which allows program analysisand profiling. Program parts which are identified as suitable forthe available accelerator are exported and sent to the server.The server optimizes these program parts for the acceleratorand provides RPC execution for the client. The client transformsits program to utilize accelerated execution on the server foroffloaded program parts. We evaluate our work with a proofof-concept implementation of BAAR that uses an Intel XeonPhi 5110P as the acceleration target and performs automaticoffloading, parallelization and vectorization of suitable programparts. The practicality of BAAR for real-world examples is shownbased on a study of stencil codes. Our results show a speedup ofup to 4 without any developer-provided hints and 5.77 withhints over the same code compiled with the Intel Compiler atoptimization level O2 and running on an Intel Xeon E5-2670machine. Based on our insights gained during implementationand evaluation we outline future directions of research, e.g.,offloading more fine-granular program parts than functions, amore sophisticated communication mechanism or introducing onstack-replacement.}}, author = {{Damschen, Marvin and Plessl, Christian}}, booktitle = {{Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems (ADAPT)}}, title = {{{Easy-to-Use On-The-Fly Binary Program Acceleration on Many-Cores}}}, year = {{2015}}, } @inproceedings{1773, author = {{Schumacher, Jörn and T. Anderson, J. and Borga, A. and Boterenbrood, H. and Chen, H. and Chen, K. and Drake, G. and Francis, D. and Gorini, B. and Lanni, F. and Lehmann-Miotto, Giovanna and Levinson, L. and Narevicius, J. and Plessl, Christian and Roich, A. and Ryu, S. and P. Schreuder, F. and Vandelli, Wainer and Vermeulen, J. and Zhang, J.}}, booktitle = {{Proc. Int. Conf. on Distributed Event-Based Systems (DEBS)}}, publisher = {{ACM}}, title = {{{Improving Packet Processing Performance in the ATLAS FELIX Project – Analysis and Optimization of a Memory-Bounded Algorithm}}}, doi = {{10.1145/2675743.2771824}}, year = {{2015}}, } @article{1768, author = {{Plessl, Christian and Platzner, Marco and Schreier, Peter J.}}, journal = {{Informatik Spektrum}}, keywords = {{approximate computing, survey}}, number = {{5}}, pages = {{396--399}}, publisher = {{Springer}}, title = {{{Aktuelles Schlagwort: Approximate Computing}}}, doi = {{10.1007/s00287-015-0911-z}}, year = {{2015}}, } @inproceedings{238, abstract = {{In this paper, we study how binary applications can be transparently accelerated with novel heterogeneous computing resources without requiring any manual porting or developer-provided hints. Our work is based on Binary Acceleration At Runtime (BAAR), our previously introduced binary acceleration mechanism that uses the LLVM Compiler Infrastructure. BAAR is designed as a client-server architecture. The client runs the program to be accelerated in an environment, which allows program analysis and profiling and identifies and extracts suitable program parts to be offloaded. The server compiles and optimizes these offloaded program parts for the accelerator and offers access to these functions to the client with a remote procedure call (RPC) interface. Our previous work proved the feasibility of our approach, but also showed that communication time and overheads limit the granularity of functions that can be meaningfully offloaded. In this work, we motivate the importance of a lightweight, high-performance communication between server and client and present a communication mechanism based on the Message Passing Interface (MPI). We evaluate our approach by using an Intel Xeon Phi 5110P as the acceleration target and show that the communication overhead can be reduced from 40% to 10%, thus enabling even small hotspots to benefit from offloading to an accelerator.}}, author = {{Damschen, Marvin and Riebler, Heinrich and Vaz, Gavin Francis and Plessl, Christian}}, booktitle = {{Proceedings of the 2015 Conference on Design, Automation and Test in Europe (DATE)}}, pages = {{1078--1083}}, publisher = {{EDA Consortium / IEEE}}, title = {{{Transparent offloading of computational hotspots from binary code to Xeon Phi}}}, doi = {{10.7873/DATE.2015.1124}}, year = {{2015}}, } @article{1775, abstract = {{The ATLAS experiment at CERN is planning full deployment of a new unified optical link technology for connecting detector front end electronics on the timescale of the LHC Run 4 (2025). It is estimated that roughly 8000 GBT (GigaBit Transceiver) links, with transfer rates up to 10.24 Gbps, will replace existing links used for readout, detector control and distribution of timing and trigger information. A new class of devices will be needed to interface many GBT links to the rest of the trigger, data-acquisition and detector control systems. In this paper FELIX (Front End LInk eXchange) is presented, a PC-based device to route data from and to multiple GBT links via a high-performance general purpose network capable of a total throughput up to O(20 Tbps). FELIX implies architectural changes to the ATLAS data acquisition system, such as the use of industry standard COTS components early in the DAQ chain. Additionally the design and implementation of a FELIX demonstration platform is presented and hardware and software aspects will be discussed.}}, author = {{Anderson, J and Borga, A and Boterenbrood, H and Chen, H and Chen, K and Drake, G and Francis, D and Gorini, B and Lanni, F and Lehmann Miotto, G and Levinson, L and Narevicius, J and Plessl, Christian and Roich, A and Ryu, S and Schreuder, F and Schumacher, Jörn and Vandelli, Wainer and Vermeulen, J and Zhang, J}}, journal = {{Journal of Physics: Conference Series}}, publisher = {{IOP Publishing}}, title = {{{FELIX: a High-Throughput Network Approach for Interfacing to Front End Electronics for ATLAS Upgrades}}}, doi = {{10.1088/1742-6596/664/8/082050}}, volume = {{664}}, year = {{2015}}, } @inbook{335, abstract = {{Im Bereich der Computersysteme ist die Festlegung der Grenze zwischen Hardware und Software eine zentrale Problemstellung. Diese Grenze hat in den letzten Jahrzehnten nicht nur die Entwicklung von Computersystemen bestimmt, sondern auch die Strukturierung der Ausbildung in den Computerwissenschaften beeinflusst und sogar zur Entstehung von neuen Forschungsrichtungen gef{\"u}hrt. In diesem Beitrag besch{\"a}ftigen wir uns mit Verschiebungen an der Grenze zwischen Hardware und Software und diskutieren insgesamt drei qualitativ unterschiedliche Formen solcher Verschiebungen. Wir beginnen mit der Entwicklung von Computersystemen im letzten Jahrhundert und der Entstehung dieser Grenze, die Hardware und Software erst als eigenst{\"a}ndige Produkte differenziert. Dann widmen wir uns der Frage, welche Funktionen in einem Computersystem besser in Hardware und welche besser in Software realisiert werden sollten, eine Fragestellung die zu Beginn der 90er-Jahre zur Bildung einer eigenen Forschungsrichtung, dem sogenannten Hardware/Software Co-design, gef{\"u}hrt hat. Im Hardware/Software Co-design findet eine Verschiebung von Funktionen an der Grenze zwischen Hardware und Software w{\"a}hrend der Entwicklung eines Produktes statt, um Produkteigenschaften zu optimieren. Im fertig entwickelten und eingesetzten Produkt hingegen k{\"o}nnen wir dann eine feste Grenze zwischen Hardware und Software beobachten. Im dritten Teil dieses Beitrags stellen wir mit selbst-adaptiven Systemen eine hochaktuelle Forschungsrichtung vor. In unserem Kontext bedeutet Selbstadaption, dass ein System Verschiebungen von Funktionen an der Grenze zwischen Hardware und Software autonom w{\"a}hrend der Betriebszeit vornimmt. Solche Systeme beruhen auf rekonfigurierbarer Hardware, einer relativ neuen Technologie mit der die Hardware eines Computers w{\"a}hrend der Laufzeit ver{\"a}ndert werden kann. Diese Technologie f{\"u}hrt zu einer durchl{\"a}ssigen Grenze zwischen Hardware und Software bzw. l{\"o}st sie die herk{\"o}mmliche Vorstellung einer festen Hardware und einer flexiblen Software damit auf.}}, author = {{Platzner, Marco and Plessl, Christian}}, booktitle = {{Logiken strukturbildender Prozesse: Automatismen}}, editor = {{Künsemöller, Jörn and Eke, Norber Otto and Foit, Lioba and Kaerlein, Timo}}, isbn = {{978-3-7705-5730-1}}, pages = {{123--144}}, publisher = {{Wilhelm Fink}}, title = {{{Verschiebungen an der Grenze zwischen Hardware und Software}}}, year = {{2014}}, }