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Disambiguation of "Pellauer, Michael"

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Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity.

, , , , , , , and . CoRR, (2022)

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Michael Pellauer

Michael Bode

Le groupe international de sociétés: le système de conflit de lois en droit comparé français et allemand. HU Berlin, (2009)

Michael Liecke

Subnationale Clusterpolitik: die Biotechnologiepolitik deutscher Länder im Vergleich. Uni München, (2009)

Michael Schoierer

NS-Diktatur, Anomie und Demokratisierung Westdeutschlands. Uni Augsburg, (2007)

Michael Krug

X-ray crystallographic analysis of the archaeal transcriptional regulator TrmB and development of a graphical user interface for the monochromatic diffraction data processing software XDS. Uni Konstanz, (2009)
 

Other publications of authors with the same name

Flexion: A Quantitative Metric for Flexibility in DNN Accelerators., , , and . IEEE Comput. Archit. Lett., 20 (1): 1-4 (2021)Buffets: An Efficient and Composable Storage Idiom for Explicit Decoupled Data Orchestration., , , , , , , , and . ASPLOS, page 137-151. ACM, (2019)Self-Adaptive Reconfigurable Arrays (SARA): Using ML to Assist Scaling GEMM Acceleration., , and . CoRR, (2021)Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators., , , , , and . ACM Trans. Archit. Code Optim., 19 (1): 6:1-6:26 (2022)TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators., , , , , and . MICRO, page 1255-1270. ACM, (2023)Symphony: Orchestrating Sparse and Dense Tensors with Hierarchical Heterogeneous Processing., , , , , , , , , and 2 other author(s). ACM Trans. Comput. Syst., (2023)Heterogeneous Dataflow Accelerators for Multi-DNN Workloads., , , , , and . HPCA, page 71-83. IEEE, (2021)Accelerating Sparse Data Orchestration via Dynamic Reflexive Tiling (Extended Abstract)., , , , , , , , , and 1 other author(s). HOPC@SPAA, page 15-16. ACM, (2023)Accelerating Sparse Data Orchestration via Dynamic Reflexive Tiling., , , , , , , , , and 1 other author(s). ASPLOS (3), page 18-32. ACM, (2023)Self adaptive reconfigurable arrays (SARA): learning flexible GEMM accelerator configuration and mapping-space using ML., , , and . DAC, page 583-588. ACM, (2022)