• Mo, March 16: Message Passing with MPI – Day I                                         Registration open here

• Tu, March 17: Message Passing with MPI – Day II                                         Registration open here

The Message Passing Interface (MPI) is the de-facto standard for programming large HPC clusters. We will introduce the basic concepts and give an overview of some advanced features. Also covered is hybrid parallelization, i.e. the combination of MPI and shared memory programming, which is gaining popularity as the number of cores per cluster node grows. Furthermore, we will introduce the TotalView debugger and a selection of performance and correctness tools (Score-P, Vampir, MUST).

• We, March 18: Shared Memory Programming with OpenMP – Day I              Registration open here

• Th, March 19: Shared Memory Programming with OpenMP – Day II              Registration open here

OpenMP http://openmp.org/ is a widely used approach for programming shared memory architectures, supported by most compilers nowadays. We will cover the basics of the programming paradigm as well as some advanced topics such as programming NUMA machines. We will also cover a selection of performance and verification tools for OpenMP. The RWTH Compute Cluster comprises a large number of big SMP machines (up to 128 cores and 2 TB of main memory) as we consider shared memory programming a vital alternative for applications that cannot be easily parallelized with MPI. We also expect a growing number of application codes to combine MPI and OpenMP for clusters of nodes with a growing number of cores.

Furthermore, we will introduce the participants to modern features of the OpenMP 4.0 standard like vectorisation and programming for accelerators and for the Many Integrated Core (MIC) Architecture.

Guest lectures and case studies complete these day’s program.

• Fr, March 20: GPGPU Programming with OpenACC                                       Registration open here

OpenACC is a directive-based programming model for accelerators which enables delegating the responsibility for low-level (e.g. CUDA or OpenCL) programming tasks to the compiler. Using the OpenACC industry standard, the programmer can offload compute-intensive loops to an attached accelerator with little effort. The open industry standard OpenACC has been introduced in November 2011 and supports accelerating regions of code in standard C, C++ and Fortran. It provides portability across operating systems, host CPUs and accelerators.

During this workshop day, we will give an overview on OpenACC while focusing on NVIDIA GPUs. We will introduce the GPU architecture. Then, we will dive into OpenACC and learn about its possibilities to accelerate code regions. We will cover topics such as offloading loops, managing data movement between host and device, tuning data movement and accesses, applying loop schedules, using multiple GPUs or interoperate with CUDA libraries. Hands-on sessions are done on the RWTH Aachen GPU (Fermi) Cluster using PGI’s OpenACC implementation.