Ph.D.-Seminar:

High Performance Computing  I (WS 26/27)

Contents: 

We will start with an introduction into basic principles and algorithms of parallel computing followed by transferring selected algorithms onto many-core architectures. We will focus on NVIDIA-GPUs using CUDA, even on multiple GPUs. The students will compare the performance of the algorithms on the GPU with performance on multi-core CPUs using OpenMP.

A tech-report has to be produced until the end of the term.

Lecturer: Prof. Gundolf Haase, Heinrichstr. 36, Zi 506, Tel. 5178,

Appointments:  Wednesday 17:30 - 19:00 in Heinrichstr. 36, SR 11.32

Time table of lectures: 
 

Oct 1, 2026 No lecture
Oct 8, 2026	Brief introduction into concepts of parallel computing: vectorization, shared/distributed resources, threads/processes. (V 0) GPU computing: What's special? (V 1, V 3) First steps in CUDA, improving scalar product (Codes, examples).
Oct 15, 2026	Comparison A100, H100, Further development improving scalar product etc. (all Codes, examples). firstSteps skalar (+BLAS, +Thrust), float_skalar, par_skalar (+MPI) densematrices_libs (+BLAS) cusolver (+cuSOLVEr, +unifies memory) GPU computing: CUDA, Matlab, python CUDA: 12.1, docu, Best Practice, Profiler, Debugger,
Oct  22, 2026	Consulting on exercise. Profiling Hardware (login from outside KFU only via  VPN): Mephisto at IMSC Remote login to servers: VPN to KFU is needed: install via VPN Service the software AnyConnect (configure as server: https://univpn.uni-graz.at;   login: KFU E-mail) Linux: use ssh -X  143.50.47.xxx to connect to compute server Windows: Install WinnSSHTerm with a guided installation of further packages (putty, winscp, X-Server)
Oct 29, 2026
Nov 5,  2026	Discussion: results of first exercise.
Nov 12, 2026 No lecture	Travel Prof. Haase (COLIBRI PhD Retreat)
Nov 19, 2026
Nov 26, 2026	Individual projects
Dec 3, 2026
Dec 10, 2026
Dec 17, 2026
Jan 7, 2027
Jan 14, 2027
Jan 21, 2027
Jan 28, 2027

Task sheets (subject  to change):

• Task 1 GPU
• Task 2 with some linear algebra
• Task 3 ??

Books:

• Learn CUDA Programming: A beginner's guide to GPU programming and parallel computing with CUDA 10.x and C/C++; Han/Sharma;Packt; 2019

Extended (old) Course Material : Follow the link. See templates.

Material for CUDA:

• NVIDIA: Hardware Donation Program
• CUDA Toolkit Documentation: all
• CUDA Toolkit 12 Download/Tutorials
• CUDA 6.5: blog by Mark Harries
• NVIDIA, CUDA, OpenCL, OpenCL for NVIDIA
• CUDA Programming:  Getting Started, Guide, Reduction in CUDA
• AMD, Radeon: Developer Center
• List of GPU-acclerated libraries; Thrust 2.5 (C++ STL in CUDA), ppt

Software/Compiler/Hardware:

• FLAMEGPU: Flexible Large Scale Agent Modelling Environment for the GPU
• Nvidia: Pascal with 3840 cores
• OpenACC (Cray, NVIDIA, PGI, CAPS), Quick Ref
• CUBLAS, CUFFT, CUSPARSE, CURAND, Thrust 2.5, CuSolver,
• LAPACK on GPU (Info): cuLA
• CUDA-Programme auch auf CPUs lauffähig
• great Course by Mike Giles (see also the guest talks)
• PetSc on GPU
• Kepler-GK110: 1, 2, 3, 4
• Tesla K80: 1,   ; Tesla K20: 1, 2, 3, Top 500
• AMD: FFirepro S1000, Kaveri (856 GFLOPS, update), hUMA, APU13,

Further Links

• Comparison GPU/CPU
• Tesla mit Fermi [16.11.2009], GF100 [18.01.2010], Tesla C2050, Quadro 6000
• Wiener Supercomputer VSC (Vienna Scientific Cluster)
• Chinease GPU-supercomputers [May 31, 2010], nebulae, auto-tuning,
• Aubrey Isle / Knights Ferry co-processor card by Intel [June 1, 2010; c't 13/2010, p.20],  comparison with fermi, Compiler, 1 TFLOP DGEMM [Nov. 16, 2011]
• AMD Llano [Oct. 19, 2010], aktuell [June 2011]
• NVIDA GPUs in servers by Cray [Sept. 22, 2010],
• next generation: Kepler and Maxwell [Sept. 22, 2010
• Chinese Tianhe-1A on rank 1 in top 500 [Oct 28. 2010]: 14336 Xeon + 7168 Tesla (2.5 PFLOPS, 4.04 MW) located at NSC in Tianjin (see Spiegel, Heise, nvidia). More details.
• BlueGene/Q with 17 cores (Heise)
• Mathematica8 supports GPU computing
• low energy supercomputer at Uni Frankfurt (Heise)
• Top 500 [June 2011] (heise)
• Oak Ridge plans with 18000 Kepler-GPUs [Oct. 11, 2011]; Titan [Oct. 30, 2012]
• MS-AMP [Feb 2012]
• Cray XC30 using Xeon Phi [Nov. 9, 2012]; Titan
• Nvida: Volta (1 TB bandwidth)
• Qarnot Computing