Parallel Scaling of parsparsecircuit3.c Tim Warburton.

Slides:



Advertisements
Similar presentations
1 Multithreaded Programming in Java. 2 Agenda Introduction Thread Applications Defining Threads Java Threads and States Examples.
Advertisements

Analysis of Algorithms: time & space Dr. Jeyakesavan Veerasamy The University of Texas at Dallas, USA.
1 What is message passing? l Data transfer plus synchronization l Requires cooperation of sender and receiver l Cooperation not always apparent in code.
© 2004 Wayne Wolf Topics Task-level partitioning. Hardware/software partitioning.  Bus-based systems.
Communication-Avoiding Algorithms Jim Demmel EECS & Math Departments UC Berkeley.
Overview Motivation Scala on LLVM Challenges Interesting Subsets.
CGrid 2005, slide 1 Empirical Evaluation of Shared Parallel Execution on Independently Scheduled Clusters Mala Ghanesh Satish Kumar Jaspal Subhlok University.
Parallel Jacobi Algorithm Steven Dong Applied Mathematics.
1 ISCM-10 Taub Computing Center High Performance Computing for Computational Mechanics Moshe Goldberg March 29, 2001.
A Process Splitting Transformation for Kahn Process Networks Sjoerd Meijer.
Distributed Systems CS
Program Analysis and Tuning The German High Performance Computing Centre for Climate and Earth System Research Panagiotis Adamidis.
Parallel Processing1 Parallel Processing (CS 667) Lecture 9: Advanced Point to Point Communication Jeremy R. Johnson *Parts of this lecture was derived.
SINAUT S S T A&D PT2 M - 04/2003 Configurations, Datatransmission Examples T e l e c o n t r o l w i t h S I M A T I C S 7 Station Control System.
SAN DIEGO SUPERCOMPUTER CENTER Blue Gene for Protein Structure Prediction (Predicting CASP Targets in Record Time) Ross C. Walker.
TOSSIM A simulator for TinyOS Presented at SenSys 2003 Presented by : Bhavana Presented by : Bhavana 16 th March, 2005.
MPI and C-Language Seminars Seminar Plan  Week 1 – Introduction, Data Types, Control Flow, Pointers  Week 2 – Arrays, Structures, Enums, I/O,
Scheduling Considerations for building Dynamic Verification Tools for MPI Sarvani Vakkalanka, Michael DeLisi Ganesh Gopalakrishnan, Robert M. Kirby School.
1 Parallel Computing—Introduction to Message Passing Interface (MPI)
Introduction  What is an Operating System  What Operating Systems Do  How is it filling our life 1-1 Lecture 1.
Process Scheduling. Process The activation of a program. Can have multiple processes of a program Entities associated with a process –Instruction pointer,
Unified Parallel C at LBNL/UCB FT Benchmark in UPC Christian Bell and Rajesh Nishtala.
Parallelization: Conway’s Game of Life. Cellular automata: Important for science Biology – Mapping brain tumor growth Ecology – Interactions of species.
Introduction to Symmetric Multiprocessors Süha TUNA Bilişim Enstitüsü UHeM Yaz Çalıştayı
Parallel Communications and NUMA Control on the Teragrid’s New Sun Constellation System Lars Koesterke with Kent Milfeld and Karl W. Schulz AUS Presentation.
Shilpa Seth.  Centralized System Centralized System  Client Server System Client Server System  Parallel System Parallel System.
Reference: / Parallel Programming Paradigm Yeni Herdiyeni Dept of Computer Science, IPB.
Parallel Processing LAB NO 1.
Ajmer Singh PGT(IP) Software Concepts. Ajmer Singh PGT(IP) Operating System It is a program which acts as an interface between a user and hardware.
UNIX System Administration OS Kernal Copyright 2002, Dr. Ken Hoganson All rights reserved. OS Kernel Concept Kernel or MicroKernel Concept: An OS architecture-design.
Independent Study of Parallel Programming Languages An Independent Study By: Haris Ribic, Computer Science - Theoretical Independent Study Advisor: Professor.
Integrating Trilinos Solvers to SEAM code Dagoberto A.R. Justo – UNM Tim Warburton – UNM Bill Spotz – Sandia.
Tools and Utilities for parallel and serial codes in ENEA-GRID environment CRESCO Project: Salvatore Raia SubProject I.2 C.R. ENEA-Portici. 11/12/2007.
STRATEGIC NAMING: MULTI-THREADED ALGORITHM (Ch 27, Cormen et al.) Parallelization Four types of computing: –Instruction (single, multiple) per clock cycle.
“elbowing out” Processors used Speedup Efficiency timeexecution Parallel Processors timeexecution Sequential Efficiency   
MA471Fall 2003 Lecture5. More Point To Point Communications in MPI Note: so far we have covered –MPI_Init, MPI_Finalize –MPI_Comm_size, MPI_Comm_rank.
Introduction, background, jargon Jakub Yaghob. Literature T.G.Mattson, B.A.Sanders, B.L.Massingill: Patterns for Parallel Programming, Addison- Wesley,
Programming Multi-Core Processors based Embedded Systems A Hands-On Experience on Cavium Octeon based Platforms Lab Exercises.
Chapter 2 Parallel Architecture. Moore’s Law The number of transistors on a chip doubles every years. – Has been valid for over 40 years – Can’t.
Parallel Computers Organizations and Architecture Department of Computer Science Southern Illinois University Edwardsville Summer, 2015 Dr. Hiroshi Fujinoki.
Parallelization of the Classic Gram-Schmidt QR-Factorization
A Distributed Algorithm for 3D Radar Imaging PATRICK LI SIMON SCOTT CS 252 MAY 2012.
Settings and properties Sergey Sukhonosov, Dr. Sergey Belov National Oceanographic Data Centre, Russia Training course on establishment of the ODP regional.
MPI Communications Point to Point Collective Communication Data Packaging.
OS2- Sem ; R. Jalili Introduction Chapter 1.
1 MA/CS471 Lecture 7 Fall 2003 Prof. Tim Warburton
Trace-Based Optimization for Precomputation and Prefetching Madhusudan Raman Supervisor: Prof. Michael Voss.
SYNAR Systems Networking and Architecture Group CMPT 886: Computer Architecture Primer Dr. Alexandra Fedorova School of Computing Science SFU.
Buddy Scheduling in Distributed Scientific Applications on SMT Processors Nikola Vouk December 20, 2004 In Fulfillment of Requirement for Master’s of Science.
Harnessing Multicore Processors for High Speed Secure Transfer Raj Kettimuthu Argonne National Laboratory.
MA471Fall 2002 Lecture5. More Point To Point Communications in MPI Note: so far we have covered –MPI_Init, MPI_Finalize –MPI_Comm_size, MPI_Comm_rank.
Part 3.  What are the general types of parallelism that we already discussed?
Benchmarks of a Weather Forecasting Research Model Daniel B. Weber, Ph.D. Research Scientist CAPS/University of Oklahoma ****CONFIDENTIAL**** August 3,
CS 351/ IT 351 Modeling and Simulation Technologies HPC Architectures Dr. Jim Holten.
1 Opportunities and Challenges of Modern Communication Architectures: Case Study with QsNet CAC Workshop Santa Fe, NM, 2004 Sameer Kumar* and Laxmikant.
System Programming Basics Cha#2 H.M.Bilal. Operating Systems An operating system is the software on a computer that manages the way different programs.
SYNAR Systems Networking and Architecture Group CMPT 886: Computer Architecture Primer Dr. Alexandra Fedorova School of Computing Science SFU.
Background Computer System Architectures Computer System Software.
Programming Parallel Hardware using MPJ Express By A. Shafi.
11 Brian Van Straalen Portable Performance Discussion August 7, FASTMath SciDAC Institute.
INTRODUCTION TO HIGH PERFORMANCE COMPUTING AND TERMINOLOGY.
Pitfalls: Time Dependent Behaviors CS433 Spring 2001 Laxmikant Kale.
NGS computation services: APIs and Parallel Jobs
Buses.
for Network Processors
User-level Distributed Shared Memory
مديريت موثر جلسات Running a Meeting that Works
Threads -For CSIT.
Question 1 How are you going to provide language and/or library (or other?) support in Fortran, C/C++, or another language for massively parallel programming.
CS Introduction to Operating Systems
Presentation transcript:

Parallel Scaling of parsparsecircuit3.c Tim Warburton

1 process per node In these tests we only use one out of two processors per node.

blackbear: 16 processors, 16 nodes

Apart from the mpi_allreduce calls, this is an almost perfect picture of parallelism

2 Processes Per Node We use both processors on each node

blackbear 8 nodes, 16 processes Notice, the prevelance of waitany. Clearly this code is not working as well as it does when running with 1 process per node.

blackbear 8 nodes, 16 processes (zoom in) I suspect that the threaded mpi communicators for the unblocked isend and irecv are competing for cpu time with the user code. Also – there could be competition for the memory bus and the network bus between the processors.

Timings for M=1024 (N=1024^2) (blackbear –O3) nodesNprocswallclock time

Timings for Two Processes Per Nodes on Los Lobos nodesNprocswallclock time Timings courtesy of Zhaoxian Zhou