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Center for Development of Advanced Computing (C-DAC)
Pune, and
Centre for Modelling Simulation and Design (CMSD),
University of Hyderabad (UoH)
are jointly organizing
four days technology workshop on “
Hybrid Computing - Coprocessors & Accelerators -
Power-aware Computing & Performance of Application Kernels
(Initiatives on Measurement of Power Consumption & Performance)
(hyPACK - 2013) ” which is scheduled from
October 15-18, 2013 at CMSD, UoH.
The workshop aims at understanding power-aware computing and performance of application kernels
on High Performance Computing Systems with Intel Xeon Phi Co-processors & GPU Accelerators.
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What is New in hypack-2013 :
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Day-1 &
Day-2 :
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HPC Cluster - Intel Xeon/Phi coprocessors, ARM multicore processor &
HPC System :
Programming on Intel Xeon-Phi Coprocessors; Xeon-Phi Coprocessor usage model : MPI vesus Offload;
Compiler and Programming model; Approaches to Vectorization - Complier Directives;
Programming Paradigms - OpenMP 4.0, Intel TBB, Intel Cilk Plus, Intel MKL;
Intel Xeon-Phi Coprocessor Architecture; System software;
Tuning Memory Allocation Performance - Huge Page Sizes; Profiling & Tuning Tools; - Measurement of
Power Consumption & Performance Issues using External Power-Off-Meter; Application Kernels- Prog. on ARM
processor systems;
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Day 3 &
Day-4 :
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An Overview of CUDA enabled NVIDIA GPUs : CUDA SDK/APIs;
CUDA - Optimization & Performance Issues; Efficient use of different memory types,
CUDA Libraries (CUBLAS, CUFFT, CULA Tools, MAGMA, CUSPARSE, Thurst);
CUDA-OpenACC APIs; NVIDIA - OpenCL; NVIDIA GPU Cluster;
An Overview of AMD Accelerated Parallel Processing (APP) Capabilities;
AMD APUs - OpenCL Prog. On Multi-Core CPUs & Multi-GPUs; AMD APP Math lib. - BLAS & FFTs;
AMD APP SDK, AMD tools - Aparapi AP; AMD OpenCL tuning - performance;
HPC AMD GPU Cluster: Host CPU (Pthreads, OpenMP 4.0, MPI) with OpenCL on AMD GPUs;
GPU Cluster - Health Monitoring
Programming on ARM Processor multi-core systems; power-aware performance
Issues on ARM processor systems; Prog. on carma - NVIDIA CUDA on ARM Develop. Kit;
An Overview of FPGA Systems; Energy Efficiency - Power-Off Meters and
NVML libraries; Power Efficient API - Perf. Issues;
Health Monitoring GPUs in Cluster;
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Apps:
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Mixed Programming for Numerical /Non-Numerical Computations on multi-core processors with
Intel Xeon-Phi coprocessors - and NVIDIA /AMD GPU accelerators and ARM processor systems;
Application & System Benchmarks & Performance; Image Processing Applications;
Bio-Informatics - String Search Algorithms & Sequence Analysis; Dense /Sparse Matrix Computations
on HPC GPU Cluster; Solution of Partial Differential Eqs. (FDM & FEM); FFT Libraries;
Invited lectures on Information Sciences & Computational Physics
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Important Dates...
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Final Announcement |
Reg. Open |
Tech. Prog.
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Early Bird Reg.
Extended
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Final Tech. Prog.
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