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Jasmin König
https://nanohub.org/members/323796
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Recursive algorithm for NEGF in Python GPU version
02 Feb 2021 | | Contributor(s):: Ning Yang, Tong Wu, Jing Guo
This folder contains two Python functions for GPU-accelerated simulation, which implements the recursive algorithm in the non-equilibrium Green’s function (NEGF) formalism. Compared to the matlab implementation [1], the GPU version allows massive parallel running over many cores on GPU...
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Sebastian Jan Juchnowski
https://nanohub.org/members/197883
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A Performance Comparison of Algebraic Multigrid Preconditioners on GPUs and MIC
04 Feb 2016 | | Contributor(s):: Karl Rupp
Algebraic multigrid (AMG) preconditioners for accelerators such as graphics processing units (GPUs) and Intel's many-integrated core (MIC) architecture typically require a careful, problem-dependent trade-off between efficient hardware use, robustness, and convergence rate in order to...
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Advanced Parallel CPU Programming Part 1: OmpSs Quick Overview
29 Aug 2013 | | Contributor(s):: NanoBio Node, Xavier Teruel
High Performance Computing --> Some basic concepts, Supercomputers nowadays, Parallel programming models OmpSs Introduction --> OmpSs main features, A Practical Example: Cholesky factorization BSC’s Implementation --> Mercurium Compiler, Nanos++ Runtime Library, Visualization Tools
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Intel Advisor XE 2013
12 Mar 2013 | | Contributor(s):: Intel
This is a presentation Intel engineer James Tullos presented at Purdue University on March 8, 2013.
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Intel Inspector XE 2013 An Introduction
12 Mar 2013 | | Contributor(s):: Holly Wilper
This is a presentation Intel engineer Holly Wilper presented at Purdue University on March 8, 2013.
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Intel VTune Amplifier XE 2013: An introduction
12 Mar 2013 | | Contributor(s):: Intel
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Intel Xeon Phi Programming
12 Mar 2013 | | Contributor(s):: James Tullos
This is a presentation Intel engineer James Tullos presented at Purdue University on March 8, 2013.
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Edoardo Emilio Coronado
https://nanohub.org/members/66233
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Mathematica for CUDA and OpenCL Programming
07 Mar 2011 | | Contributor(s):: Ulises Cervantes-Pimentel, Abdul Dakkak
In the latest release of Mathematica 8, a large number of programming tools for GPU computing are available. In this presentation, new tools for CUDA and OpenCL programming will be explored. Several applications, including image processing, medical imaging, multi-gpu, statistics and finance will...
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Illinois ECE 498AL: Programming Massively Parallel Processors, Lecture 10: Control Flow
01 Sep 2009 | | Contributor(s):: Wen-Mei W Hwu
Control FlowTopics: Terminology Review How Thread Blocks are Partitioned Control Flow Instructions Parallel Reduction A Vector Reduction Example A simple Implementation Vector Reduction With Bank Conflicts Vector Reduction With Branch Divergence Predicted Execution Concept Instruction Prediction...
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Illinois ECE 498AL: Programming Massively Parallel Processors, Lecture 9: Memory Hardware in G80
30 Aug 2009 | | Contributor(s):: Wen-Mei W Hwu
Memory Hardware in G80Topics: CUDA Device Memory Space Parallel Memory Sharing SM Memory Architecture SM Register File Programmer view of Register File Matrix Multiplication Example More on Dynamic Partitioning ILP vs. TLP Memory Layout of a Matrix in C Constants Shared Memory Parallel Memory...
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Illinois ECE 498AL: Programming Massively Parallel Processors, Lecture 6: CUDA Memories - Part 2
20 Aug 2009 | | Contributor(s):: Wen-Mei W Hwu
CUDA Memories Part2Topics: Tiled Multiply Breaking Md and Nd into Tiles Tiled Matrix Multiplication Kernel CUDA Code - Kernel Execution Configuration First Order Size considerations in G80 G80 Shared Memory and Threading Tiling Size Effects Typical Structure of a CUDA ProgramThese lecture were...
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Illinois ECE 498AL: Programming Massively Parallel Processors
11 Aug 2009 | | Contributor(s):: Wen-Mei W Hwu
Spring 2009 Virtually all semiconductor market domains, including PCs, game consoles, mobile handsets, servers, supercomputers, and networks, are converging to concurrent platforms. There are two important reasons for this trend. First, these concurrent processors can potentially offer more...
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The Multicore Era: Crisis or (and?) Opportunity?
27 Mar 2009 | | Contributor(s):: Mithuna Thottethodi
This talk will provide a brief overview of how we got to the multicore era, the implications and challenges for hardware/software developers and users, and some informed speculation on where the trends may be headed.
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Charles Taylor Patrick Gillespie
Mr. Charles Taylor Patrick Gillespie is currently pursuing a LL.M. in Intellectual Property at Santa Clara University School of Law and focusing on Nanotechnology and the Law. He graduated from the...
https://nanohub.org/members/33082
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MPI for the Next Generation of Supercomputing
05 Dec 2008 | | Contributor(s):: Andrew Lumsdaine
Despite premature rumours of its demise, MPI continues to be the de facto standard for high-performance parallel computing. Nonetheless, supercomputing software and the high-end ecosystem continue to advance, creating challenges to several aspects of MPI. In this talk we will review the design...
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OpenMP Tutorial
25 Nov 2008 | | Contributor(s):: Seung-Jai Min
This tutorial consists of three parts. First, we will discuss abouthow OpenMP is typically used and explain OpenMP programming model. Second, we will describe important OpenMP constructs and data enviroments. Finally, we will show a simple example to illustrate how OpenMP APIs are used to program...
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Purdue School on High Performance and Parallel Computing
24 Nov 2008 | | Contributor(s):: Alejandro Strachan, Faisal Saied
The goal of this workshop is to provide training in the area of high performance scientific computing for graduate students and researchers interested in scientific computing. The School will address current hardware and software technologies and trends for parallel computing and their...