Non quia difficilia sunt non audemus, sed quia non audemus difficilia sunt
Home -> Publications
all years
    edited volumes
  Full CV [pdf]


  Past Events

Publications of Torsten Hoefler
Copyright Notice:

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

T. Hoefler:

 Progress in automatic GPU compilation and why you want to run MPI on your GPU.

(Presentation - presented in Cetraro, Italy, Jun. 2016, Invited talk at the Cetraro HPC conference )


Auto-parallelization of programs that have not been developed with parallelism in mind is one of the holy grails in computer science. It requires understanding the source code's data flow to automatically distribute the data, parallelize the computations, and infer synchronizations where necessary. We will discuss our new LLVM-based research compiler Polly-ACC that enables automatic compilation to accelerator devices such as GPUs. Unfortunately, its applicability is limited to codes for which the iteration space and all accesses can be described as affine functions. In the second part of the talk, we will discuss dCUDA, a way to express parallel codes in MPI-RMA, a well-known communication library, to map them automatically to GPU clusters. The dCUDA approach enables simple and portable programming across heterogeneous devices due to programmer-specified locality. Furthermore, dCUDA enables hardware-supported overlap of computation and communication and is applicable to next-generation technologies such as NVLINK. We will demonstrate encouraging initial results and show limitations of current devices in order to start a discussion.


download slides:

Recorded talk (best effort)



  author={T. Hoefler},
  title={{Progress in automatic GPU compilation and why you want to run MPI on your GPU.}},
  location={Cetraro, Italy},
  note={Invited talk at the Cetraro HPC conference},

serving:© Torsten Hoefler