@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}}, } @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}}, } @inproceedings{439, abstract = {{Reconfigurable architectures provide an opportunityto accelerate a wide range of applications, frequentlyby exploiting data-parallelism, where the same operations arehomogeneously executed on a (large) set of data. However, whenthe sequential code is executed on a host CPU and only dataparallelloops are executed on an FPGA coprocessor, a sufficientlylarge number of loop iterations (trip counts) is required, such thatthe control- and data-transfer overheads to the coprocessor canbe amortized. However, the trip count of large data-parallel loopsis frequently not known at compile time, but only at runtime justbefore entering a loop. Therefore, we propose to generate codeboth for the CPU and the coprocessor, and to defer the decisionwhere to execute the appropriate code to the runtime of theapplication when the trip count of the loop can be determinedjust at runtime. We demonstrate how an LLVM compiler basedtoolflow can automatically insert appropriate decision blocks intothe application code. Analyzing popular benchmark suites, weshow that this kind of runtime decisions is often applicable. Thepractical feasibility of our approach is demonstrated by a toolflowthat automatically identifies loops suitable for vectorization andgenerates code for the FPGA coprocessor of a Convey HC-1. Thetoolflow adds decisions based on a comparison of the runtimecomputedtrip counts to thresholds for specific loops and alsoincludes support to move just the required data to the coprocessor.We evaluate the integrated toolflow with characteristic loopsexecuted on different input data sizes.}}, author = {{Vaz, Gavin Francis and Riebler, Heinrich and Kenter, Tobias and Plessl, Christian}}, booktitle = {{Proceedings of the International Conference on ReConFigurable Computing and FPGAs (ReConFig)}}, pages = {{1--8}}, publisher = {{IEEE}}, title = {{{Deferring Accelerator Offloading Decisions to Application Runtime}}}, doi = {{10.1109/ReConFig.2014.7032509}}, year = {{2014}}, } @inproceedings{406, abstract = {{Stereo-matching algorithms recently received a lot of attention from the FPGA acceleration community. Presented solutions range from simple, very resource efficient systems with modest matching quality for small embedded systems to sophisticated algorithms with several processing steps, implemented on big FPGAs. In order to achieve high throughput, most implementations strongly focus on pipelining and data reuse between different computation steps. This approach leads to high efficiency, but limits the supported computation patterns and due the high integration of the implementation, adaptions to the algorithm are difficult. In this work, we present a stereo-matching implementation, that starts by offloading individual kernels from the CPU to the FPGA. Between subsequent compute steps on the FPGA, data is stored off-chip in on-board memory of the FPGA accelerator card. This enables us to accelerate the AD-census algorithm with cross-based aggregation and scanline optimization for the first time without algorithmic changes and for up to full HD image dimensions. Analyzing throughput and bandwidth requirements, we outline some trade-offs that are involved with this approach, compared to tighter integration of more kernel loops into one design.}}, author = {{Kenter, Tobias and Schmitz, Henning and Plessl, Christian}}, booktitle = {{Proceedings of the International Conference on ReConFigurable Computing and FPGAs (ReConFig)}}, pages = {{1--8}}, publisher = {{IEEE}}, title = {{{Kernel-Centric Acceleration of High Accuracy Stereo-Matching}}}, doi = {{10.1109/ReConFig.2014.7032535}}, year = {{2014}}, } @inproceedings{1781, abstract = {{In light of an increasing awareness of environmental challenges, extensive research is underway to develop new light-weight materials. A problem arising with these materials is their increased response to vibration. This can be solved using a new composite material that contains embedded hollow spheres that are partially filled with particles. Progress on the adaptation of molecular dynamics towards a particle-based numerical simulation of this material is reported. This includes the treatment of specific boundary conditions and the adaption of the force computation. First results are presented that showcase the damping properties of such particle-filled spheres in a bouncing experiment.}}, author = {{Steinle, Tobias and Vrabec, Jadran and Walther, Andrea}}, booktitle = {{Proc. Modeling, Simulation and Optimization of Complex Processes (HPSC)}}, editor = {{Bock, Hans Georg and Hoang, Xuan Phu and Rannacher, Rolf and Schlöder, Johannes P.}}, isbn = {{978-3-319-09063-4}}, pages = {{233--243}}, publisher = {{Springer International Publishing}}, title = {{{Numerical Simulation of the Damping Behavior of Particle-Filled Hollow Spheres}}}, doi = {{10.1007/978-3-319-09063-4_19}}, year = {{2014}}, } @inproceedings{1782, author = {{Graf, Tobias and Schaefers, Lars and Platzner, Marco}}, booktitle = {{Proc. Conf. on Computers and Games (CG)}}, number = {{8427}}, pages = {{14--25}}, publisher = {{Springer}}, title = {{{On Semeai Detection in Monte-Carlo Go}}}, doi = {{10.1007/978-3-319-09165-5_2}}, year = {{2014}}, } @inproceedings{388, abstract = {{In order to leverage the use of reconfigurable architectures in general-purpose computing, quick and automated methods to find suitable accelerator designs are required. We tackle this challenge in both regards. In order to avoid long synthesis times, we target a vector copro- cessor, implemented on the FPGAs of a Convey HC-1. Previous studies showed that existing tools were not able to accelerate a real-world application with low effort. We present a toolflow to automatically identify suitable loops for vectorization, generate a corresponding hardware/software bipartition, and generate coprocessor code. Where applicable, we leverage outer-loop vectorization. We evaluate our tools with a set of characteristic loops, systematically analyzing different dependency and data layout properties.}}, author = {{Kenter, Tobias and Vaz, Gavin Francis and Plessl, Christian}}, booktitle = {{Proceedings of the International Symposium on Reconfigurable Computing: Architectures, Tools, and Applications (ARC)}}, pages = {{144--155}}, publisher = {{Springer International Publishing}}, title = {{{Partitioning and Vectorizing Binary Applications for a Reconfigurable Vector Computer}}}, doi = {{10.1007/978-3-319-05960-0_13}}, volume = {{8405}}, year = {{2014}}, } @inproceedings{377, abstract = {{In this paper, we study how AES key schedules can be reconstructed from decayed memory. This operation is a crucial and time consuming operation when trying to break encryption systems with cold-boot attacks. In software, the reconstruction of the AES master key can be performed using a recursive, branch-and-bound tree-search algorithm that exploits redundancies in the key schedule for constraining the search space. In this work, we investigate how this branch-and-bound algorithm can be accelerated with FPGAs. We translated the recursive search procedure to a state machine with an explicit stack for each recursion level and create optimized datapaths to accelerate in particular the processing of the most frequently accessed tree levels. We support two different decay models, of which especially the more realistic non-idealized asymmetric decay model causes very high runtimes in software. Our implementation on a Maxeler dataflow computing system outperforms a software implementation for this model by up to 27x, which makes cold-boot attacks against AES practical even for high error rates.}}, author = {{Riebler, Heinrich and Kenter, Tobias and Plessl, Christian and Sorge, Christoph}}, booktitle = {{Proceedings of Field-Programmable Custom Computing Machines (FCCM)}}, keywords = {{coldboot}}, pages = {{222--229}}, publisher = {{IEEE}}, title = {{{Reconstructing AES Key Schedules from Decayed Memory with FPGAs}}}, doi = {{10.1109/FCCM.2014.67}}, year = {{2014}}, } @inproceedings{1778, author = {{C. Durelli, Gianluca and Pogliani, Marcello and Miele, Antonio and Plessl, Christian and Riebler, Heinrich and Vaz, Gavin Francis and D. Santambrogio, Marco and Bolchini, Cristiana}}, booktitle = {{Proc. Int. Symp. on Parallel and Distributed Processing with Applications (ISPA)}}, pages = {{142--149}}, publisher = {{IEEE}}, title = {{{Runtime Resource Management in Heterogeneous System Architectures: The SAVE Approach}}}, doi = {{10.1109/ISPA.2014.27}}, year = {{2014}}, } @inproceedings{1780, author = {{C. Durelli, Gianluca and Copolla, Marcello and Djafarian, Karim and Koranaros, George and Miele, Antonio and Paolino, Michele and Pell, Oliver and Plessl, Christian and D. Santambrogio, Marco and Bolchini, Cristiana}}, booktitle = {{Proc. Int. Conf. on Reconfigurable Computing: Architectures, Tools and Applications (ARC)}}, publisher = {{Springer}}, title = {{{SAVE: Towards efficient resource management in heterogeneous system architectures}}}, doi = {{10.1007/978-3-319-05960-0_38}}, year = {{2014}}, } @inproceedings{1788, author = {{Berenbrink, Petra and Brinkmann, André and Friedetzky, Tom and Meister, Dirk and Nagel, Lars}}, booktitle = {{Proc. Int. Symp. on Parallel and Distributed Processing Workshops (IPDPSW)}}, publisher = {{IEEE}}, title = {{{Distributing Storage in Cloud Environments}}}, doi = {{10.1109/IPDPSW.2013.148}}, year = {{2013}}, } @inproceedings{1793, author = {{Meister, Dirk and Brinkmann, André and Süß, Tim}}, booktitle = {{Proc. USENIX Conference on File and Storage Technologies (FAST)}}, pages = {{175--182}}, publisher = {{USENIX Association}}, title = {{{File Recipe Compression in Data Deduplication Systems}}}, year = {{2013}}, } @inproceedings{1786, author = {{Kasap, Server and Redif, Soydan}}, booktitle = {{Proc. IEEE Signal Processing and Communications Conf. (SUI)}}, publisher = {{IEEE}}, title = {{{FPGA Implementation of a Second-Order Convolutive Blind Signal Separation Algorithm}}}, doi = {{10.1109/SIU.2013.6531530}}, year = {{2013}}, } @inproceedings{528, abstract = {{Cold-boot attacks exploit the fact that DRAM contents are not immediately lost when a PC is powered off. Instead the contents decay rather slowly, in particular if the DRAM chips are cooled to low temperatures. This effect opens an attack vector on cryptographic applications that keep decrypted keys in DRAM. An attacker with access to the target computer can reboot it or remove the RAM modules and quickly copy the RAM contents to non-volatile memory. By exploiting the known cryptographic structure of the cipher and layout of the key data in memory, in our application an AES key schedule with redundancy, the resulting memory image can be searched for sections that could correspond to decayed cryptographic keys; then, the attacker can attempt to reconstruct the original key. However, the runtime of these algorithms grows rapidly with increasing memory image size, error rate and complexity of the bit error model, which limits the practicability of the approach.In this work, we study how the algorithm for key search can be accelerated with custom computing machines. We present an FPGA-based architecture on a Maxeler dataflow computing system that outperforms a software implementation up to 205x, which significantly improves the practicability of cold-attacks against AES.}}, author = {{Riebler, Heinrich and Kenter, Tobias and Sorge, Christoph and Plessl, Christian}}, booktitle = {{Proceedings of the International Conference on Field-Programmable Technology (FPT)}}, keywords = {{coldboot}}, pages = {{386--389}}, publisher = {{IEEE}}, title = {{{FPGA-accelerated Key Search for Cold-Boot Attacks against AES}}}, doi = {{10.1109/FPT.2013.6718394}}, year = {{2013}}, } @inproceedings{1784, author = {{Kaiser, Jürgen and Meister, Dirk and Gottfried, Viktor and Brinkmann, André}}, booktitle = {{Proc. IEEE Int. Conf. on Networking, Architecture and Storage (NAS)}}, pages = {{88--97}}, publisher = {{IEEE Computer Society}}, title = {{{MCD: Overcoming the Data Download Bottleneck in Data Centers}}}, doi = {{10.1109/NAS.2013.18}}, year = {{2013}}, } @inproceedings{505, abstract = {{In this paper we introduce “On-The-Fly Computing”, our vision of future IT services that will be provided by assembling modular software components available on world-wide markets. After suitable components have been found, they are automatically integrated, configured and brought to execution in an On-The-Fly Compute Center. We envision that these future compute centers will continue to leverage three current trends in large scale computing which are an increasing amount of parallel processing, a trend to use heterogeneous computing resources, and—in the light of rising energy cost—energy-efficiency as a primary goal in the design and operation of computing systems. In this paper, we point out three research challenges and our current work in these areas.}}, author = {{Happe, Markus and Kling, Peter and Plessl, Christian and Platzner, Marco and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 9th IEEE Workshop on Software Technology for Future embedded and Ubiquitous Systems (SEUS)}}, publisher = {{IEEE}}, title = {{{On-The-Fly Computing: A Novel Paradigm for Individualized IT Services}}}, doi = {{10.1109/ISORC.2013.6913232}}, year = {{2013}}, } @inproceedings{1787, author = {{Suess, Tim and Schoenrock, Andrew and Meisner, Sebastian and Plessl, Christian}}, booktitle = {{Proc. Int. Symp. on Parallel and Distributed Processing Workshops (IPDPSW)}}, isbn = {{978-0-7695-4979-8}}, pages = {{64--73}}, publisher = {{IEEE Computer Society}}, title = {{{Parallel Macro Pipelining on the Intel SCC Many-Core Computer}}}, doi = {{10.1109/IPDPSW.2013.136}}, year = {{2013}}, } @inproceedings{2107, author = {{Grunzke, Richard and Birkenheuer, Georg and Blunk, Dirk and Breuers, Sebastian and Brinkmann, André and Gesing, Sandra and Herres-Pawlis, Sonja and Kohlbacher, Oliver and Krüger, Jens and Kruse, Martin and Müller-Pfefferkorn, Ralph and Schäfer, Patrick and Schuller, Bernd and Steinke, Thomas and Zink, Andreas}}, booktitle = {{Proc. UNICORE Summit}}, title = {{{A Data Driven Science Gateway for Computational Workflows}}}, year = {{2012}}, } @inproceedings{2178, author = {{Gesing, Sandra and Herres-Pawlis, Sonja and Birkenheuer, Georg and Brinkmann, André and Grunzke, Richard and Kacsuk, Peter and Kohlbacher, Oliver and Kozlovszky, Miklos and Krüger, Jens and Müller-Pfefferkorn, Ralph and Schäfer, Patrick and Steinke, Thomas}}, booktitle = {{Proceedings of Science}}, title = {{{A Science Gateway Getting Ready for Serving the International Molecular Simulation Community}}}, volume = {{PoS(EGICF12-EMITC2)050}}, year = {{2012}}, } @inproceedings{2099, author = {{Meister, Dirk and Kaiser, Jürgen and Brinkmann, André and Kuhn, Michael and Kunkel, Julian and Cortes, Toni}}, booktitle = {{Proc. Int. Conf. on Supercomputing (SC)}}, pages = {{7:1--7:11}}, publisher = {{IEEE Computer Society}}, title = {{{A Study on Data Deduplication in HPC Storage Systems}}}, doi = {{10.1109/SC.2012.14}}, year = {{2012}}, }