# Presentation: 800766

##  Climate/PERC Access Grid Meeting

**Pat Worley**
**Oak Ridge National Laboratory**
**10/07/2002**

## Agenda

-   Brief PERC Overview
-   Introduction of Participants and their Research Interests
-   Other Presentations

##  The Performance Evaluation Research Center (PERC)

**Participating Institutions:**
- Argonne Natl. Lab.		Univ. of California, San Diego
- Lawrence Berkeley Natl. Lab.	Univ. of Illinois
- Lawrence Livermore Natl. Lab.	Univ. of Maryland
- Oak Ridge Natl. Lab.		Univ. of Tennessee, Knoxville
**Website:  http://perc.nersc.gov**

## PERC Overview

-   An “Integrated Software Infrastructure Center” (ISIC)     sponsored under DoE’s SciDAC program.
-   Funding: approx. $2.4 million per year.
-   Mission:
-   Develop a science of performance.
-   Engineer tools for performance analysis and optimization.
-   Focus:
-   Large, grand-challenge calculations, especially SciDAC       application projects.

## Specific Objectives

-   Understand key factors in applications that affect     performance.
-   Understand key factors in computer systems that affect    performance.
-   Develop models that accurately predict performance of    applications on systems.
-   Develop an enabling infrastructure of tools for     performance monitoring, modeling and optimization.
-   Validate these ideas and infrastructure via close    collaboration with DOE Office of Science and others.
-   Transfer the technology to end users.

## New Capabilities

**  ****Better Benchmarks:**
-   Polished, concise versions of real user codes, representing    strategic application areas.
-   Kernel benchmarks extracted from real codes reduce    complexity of analyzing full-size benchmarks.
-   Low-level benchmarks measure key rates of data access at    various levels of memory hierarchy.
**  ****Modern performance monitoring tools:**
-   Flexible instrumentation systems capture hardware and    software interactions, instruction execution frequencies,    memory reference behavior, and execution overheads.
-   An advanced data management infrastructure tracks   performance experiments and data across time and space.

## New Capabilities, cont.

**  ****Performance modeling:**
*  **Application signature* tools characterize applications    independent of the machine where they execute.
*  **Machine signature* tools characterize computer systems,    independent of the applications.
*  **Convolution*** **tools combine application and machine    signatures to provide accurate performance models.
*  **Statistical models* find approximate performance models    based on easily measured performance data.
*  **Phase models* analyze separate sections of an application,    providing overall performance predictions.
*  **Performance bound* tools determine ultimate potential of an    application on a given system.

## New Capabilities, cont.

**  ****Performance optimization:**
*  **Compile-time optimization* mechanisms analyze source     code to improve performance.
*  **Self-tuning software* automatically tunes code based on    real-time measurements of hardware environment.
*  **Performance assertions* permit user-specified run-time tests    to possibly change the course of the computation    depending on results.
*  **Performance portability* programming techniques to insure    that code runs at near-optimal performance across a variety    of modern systems.

## Performance Analysis

| 
 The Parallel Climate Transitional Model (PCTM), from the  Climate modeling center, is the next generation of the  Parallel Climate Model.  It is made up of atmosphere, ocean,  land surface, river transport, and sea ice component models, 
                                                                                             and a coupler to exchange fluxes between                                                                                              the component models.

                                                                                             The code has been ported to IBM,                                                                                              Compaq, and Intel platforms.  Detailed                                                                                              performance analysis has been done using                                                                                              4 to 64 processors of an IBM SP using SvPablo.
 |
| --- |

**Performance Analysis**
**PCTM – a climate modeling code**

## Other Example Analyses:EVH1 -- a high-energy physics code

| 
 Aggregate performance measures  over all tasks for a .1 simulation- second run. Collected with PAPI on  an IBM SP (Nighthawk II / 375MHz). 
    |
| --- |

**Other Example Analyses:****EVH1 -- a high-energy physics code**

## Other Tools:

**Other Tools:**
**PAPI Perfometer Interface**

## Working with PERC

-   Benchmarking
-   Application group works with PERC to specify relevant     benchmark codes and problems.
-   PERC characterizes performance, generates performance     models, and suggests optimizations.
-   Performance Tools
-   PERC trains application developers to use tools.
-   Application group uses tools in development, providing     feedback on functionality and future development
**For further information:   http://perc.nersc.gov**

## Current Status

-   Benchmarking
-   PCTM  (ORNL, NERSC)
-   CAM2.0 (ORNL)
-   POP1.4.3 (ORNL, Illinois)
-  (POP2.0beta)
-   Performance Tools
-   PCTM (Illinois)
-   POP1.4.3 (Illinois)
-   CCSM2.0 (Maryland)

## Performance Progress

## Benchmarking

## Issues

- Can the IBM performance be improved?