Previous Semester

Paralleles Rechnen Seminar

Instructors: Univ-Prof. Dr. Bertil Schmidt
Shortname: 08.079.590
Course No.: 08.079.590
Course Type: Seminar

Requirements / organisational issues

Prerequisites:

Successful partitication in PAA or HPC.

Contents

Topic Selection:

E-Mail your two preferred topics to  Prof. Dr. Bertil Schmidt by 12th July 2019 latest. 
I will then assign a topic to you.
Note: There is also the otion of suggesting a topic by yourself (needs my approval)

Topics:

  • Accelerating Reduction and Scan Using Tensor Core Units
  • diBELLA: Distributed Long Read to Long Read Alignment
  • Performance extraction and suitability analysis of multi- and many-core architectures for next generation sequencing secondary analysis
  • Adaptive Sparse Matrix-Matrix Multiplication on the GPU
  • GPU-Accelerated Large-Scale Genome Assembly
  • Hardware-conscious Hash-Joins on GPUs
  • Harnessing GPU tensor cores for fast FP16 arithmetic to speed up mixed-precision iterative refinement solvers
  • GRASShopPER—An algorithm for de novo assembly based on GPU alignments
  • Exascale Deep Learning for Climate Analytics
  • Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems
  • A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning
  • UPC++: A High-Performance Communication Framework for Asynchronous Computation
  • Large-Scale Hierarchical k-means for Heterogeneous Many-Core Supercomputers
  • A Framework for the Automatic Vectorization of Parallel Sort on x86-based Processors
  • self-suggested topic (needs approval)