@article{AicheReinertSchuetteetal.2012, author = {Aiche, Stephan and Reinert, Knut and Sch{\"u}tte, Christof and Hildebrand, Diana and Schl{\"u}ter, Hartmut and Conrad, Tim}, title = {Inferring Proteolytic Processes from Mass Spectrometry Time Series Data Using Degradation Graphs}, volume = {7}, journal = {PLoS ONE}, number = {7}, publisher = {Public Library of Science}, doi = {10.1371/journal.pone.0040656}, pages = {e40656}, year = {2012}, language = {en} } @article{BauerRotherMooretal.2009, author = {Bauer, Raphael and Rother, Kristian and Moor, Peter and Reinert, Knut and Steinke, Thomas and Bujnicki, Janusz and Preissner, Robert}, title = {Fast Structural Alignment of Biomolecules Using a Hash Table, N-Grams and String Descriptors}, volume = {2}, journal = {Algorithms}, number = {2}, doi = {10.3390/a2020692}, pages = {692 -- 709}, year = {2009}, language = {en} } @article{LeserHilbrichDraxletal.2021, author = {Leser, Ulf and Hilbrich, Marcus and Draxl, Claudia and Eisert, Peter and Grunske, Lars and Hostert, Patrick and Kainm{\"u}ller, Dagmar and Kao, Odej and Kehr, Birte and Kehrer, Timo and Koch, Christoph and Markl, Volker and Meyerhenke, Henning and Rabl, Tilmann and Reinefeld, Alexander and Reinert, Knut and Ritter, Kerstin and Scheuermann, Bj{\"o}rn and Schintke, Florian and Schweikardt, Nicole and Weidlich, Matthias}, title = {The Collaborative Research Center FONDA}, volume = {21}, journal = {Datenbank-Spektrum}, number = {3}, doi = {10.1007/s13222-021-00397-5}, pages = {255 -- 260}, year = {2021}, language = {en} } @inproceedings{KnaustSeilerReinertetal.2022, author = {Knaust, Marius and Seiler, Enrico and Reinert, Knut and Steinke, Thomas}, title = {Co-Design for Energy Efficient and Fast Genomic Search: Interleaved Bloom Filter on FPGA}, booktitle = {FPGA '22: Proceedings of the 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays}, doi = {10.1145/3490422.3502366}, pages = {180 -- 189}, year = {2022}, abstract = {Next-Generation Sequencing technologies generate a vast and exponentially increasing amount of sequence data. The Interleaved Bloom Filter (IBF) is a novel indexing data structure which is state-of-the-art for distributing approximate queries with an in-memory data structure. With it, a main task of sequence analysis pipelines, (approximately) searching large reference data sets for sequencing reads or short sequence patterns like genes, can be significantly accelerated. To meet performance and energy-efficiency requirements, we chose a co-design approach of the IBF data structure on the FPGA platform. Further, our OpenCL-based implementation allows a seamless integration into the widely used SeqAn C++ library for biological sequence analysis. Our algorithmic design and optimization strategy takes advantage of FPGA-specific features like shift register and the parallelization potential of many bitwise operations. We designed a well-chosen schema to partition data across the different memory domains on the FPGA platform using the Shared Virtual Memory concept. We can demonstrate significant improvements in energy efficiency of up to 19x and in performance of up to 5.6x, respectively, compared to a well-tuned, multithreaded CPU reference.}, language = {en} }