Wstęp do Modelu Standardowego

Wydział Fizyki i Informatyki Stosowanej

Wykład poświęcony jest wprowadzeniu do Modelu Standardowego opusującego naszą obecną wiedzę na temat fundamentalnych składników materii oraz ich oddziaływaniu. Poza nieco uproszczonym wstępem do teorii Modelu (nie jestem teoretykiem!) przedstawię również wybrane fakty eksperymentalne omawiając przy tym analizy prowadzone obecnie w mojej grupie - ekpseryment LHCb, pracujący przy Wielkim Zderzaczu Hadronów. Z uwagi na obecną sytuację pandemiczną wszystkie zajęcia odbywają się zdalnie przy użyciu platformy wirtualnej MS-Teams. Wszystkie materiały dotyczące zajęć (wykłady oraz notatki) będą umieszczone na naszej grupie roboczej.

Wykłady odbywają się w poniedziałki zgodnie z planem utworzonym w kalendarzu Teams. Komunikacja będzie prowadzona przy użyciu kanałów w Teams.

Pakiet ROOT - do analizy danych.

ROOT framework descritpion

PYTHON in the Enterprise

Lecture for WFiIS and Erasmus

The winter is coming..., here you get another season of the PitE 2020.
Since the present situation of the global pandemic forced us to continue the remote teaching all the information regarding the course and materials are posted in our communication channels on the MS-Teams.

Projects Area Also Teams!

This year we are offering interested students a number of projects related to scientific software development in collaboration with the University of Cincinnati. If you are interested ask me!

The lectures will be held on Fridays according to the Teams calendar.

Must see..., Home of Python

Python - Quick Fix

Introduction to CUDA and OpenCL

Erasmus and inter-depertment

We are living in a multicore world - let's use it to our advantage! This is an introductory course dedicated to massively parallel processing with CUDA C/C++. We are going to work on Linux using Nsight RAD environment. You are welcome of course to use Win/MacOS if you have some experience.
Thanks to the NVIDIA academic ambassadorship programme each enrolled student will get a chance to obtain a Certificate of Competence regarding the acceleration of computing. We will have a chance to work with the top quality materials during our labs.
Since the present situation of the global pandemic forced us to continue the remote teaching all the information regarding the course and materials are posted in our communication channels on the MS-Teams.

Computer labs - see the description on the Teams

PROJECTS

There are three distinct trajectories for preparing the "project" part for this lecture series. Depending on your interest I propose the following:

• Easy way: the reports and code written during our labs (all tasks must be solved) will be accepted as a part of the project
• Regular way: prepare a toolkit application for linear algebra operations, eg., vectors/matrices adding/subtracting, multiplication, dot product, matrix inverse (eigen values - may be challenging). The app should have a basic manager class that delegates the tasks specified by the user. Each GPU code should have its single threaded counterpart to check the performance (results and timing).
• Challenging way: for ambitious ones - there are two interesting problems that are of very practical use. The first one is accelerating the code for pattern matching - this problem is of a general nature but actually we want to focus on a particular case of retina stimulation experiments. The second is related to the advanced data anaysis techniques and pertains to accelerating the Kernel Density Estimation code. The seeding code will be made available for you (single-threaded implementation), so you will have a well defined starting point for your analysis.

Soon, I will be gathering your declarations regarding the projects!

The detailed schedule of the classes is posted on our communication channel in Teams.

The best source of knowledge is the lecture itself and NVIDIA web page. Please visit our departmental library, we have some cool books on CUDA

NVIDIA