Optimizing HPC Applications with Intel Cluster Tools : : Hunting Petaflops.

Optimizing HPC Applications with Intel Cluster Tools : : Hunting Petaflops.

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Bibliographic Details
:
Supalov, Alexander.
TeilnehmendeR:
Semin, Andrey.
Dahnken, Christopher.
Klemm, Michael.
Place / Publishing House:Berkeley, CA : : Apress L. P.,, 2014.
Ã2014.
Year of Publication:2014
Edition:1st ed.
Language:English
Online Access:
Physical Description:1 online resource (291 pages)
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Table of Contents:
  • Intro
  • Contents at a Glance
  • Contents
  • About the Authors
  • About the Technical Reviewers
  • Acknowledgments
  • Foreword
  • Introduction
  • Chapter 1: No Time to Read This Book?
  • Using Intel MPI Library
  • Using Intel Composer XE
  • Tuning Intel MPI Library
  • Gather Built-in Statistics
  • Optimize Process Placement
  • Optimize Thread Placement
  • Tuning Intel Composer XE
  • Analyze Optimization and Vectorization Reports
  • Use Interprocedural Optimization
  • Summary
  • References
  • Chapter 2: Overview of Platform Architectures
  • Performance Metrics and Targets
  • Latency, Throughput, Energy, and Power
  • Peak Performance as the Ultimate Limit
  • Scalability and Maximum Parallel Speedup
  • Bottlenecks and a Bit of Queuing Theory
  • Roofline Model
  • Performance Features of Computer Architectures
  • Increasing Single-Threaded Performance: Where You Can and Cannot Help
  • Process More Data with SIMD Parallelism
  • Distributed and Shared Memory Systems
  • Use More Independent Threads on the Same Node
  • Don't Limit Yourself to a Single Server
  • HPC Hardware Architecture Overview
  • A Multicore Workstation or a Server Compute Node
  • Coprocessor for Highly Parallel Applications
  • Group of Similar Nodes Form an HPC Cluster
  • Other Important Components of HPC Systems
  • Summary
  • References
  • Chapter 3: Top-Down Software Optimization
  • The Three Levels and Their Impact on Performance
  • System Level
  • Application Level
  • Working Against the Memory Wall
  • The Magic of Vectors
  • Distributed Memory Parallelization
  • Shared Memory Parallelization
  • Other Existing Approaches and Methods
  • Microarchitecture Level
  • Addressing Pipelines and Execution
  • Closed-Loop Methodology
  • Workload, Application, and Baseline
  • Iterating the Optimization Process
  • Summary
  • References
  • Chapter 4: Addressing System Bottlenecks.
  • Classifying System-Level Bottlenecks
  • Identifying Issues Related to System Condition
  • Characterizing Problems Caused by System Configuration
  • Understanding System-Level Performance Limits
  • Checking General Compute Subsystem Performance
  • Testing Memory Subsystem Performance
  • Testing I/O Subsystem Performance
  • Characterizing Application System-Level Issues
  • Selecting Performance Characterization Tools
  • Monitoring the I/O Utilization
  • Analyzing Memory Bandwidth
  • Summary
  • References
  • Chapter 5: Addressing Application Bottlenecks: Distributed Memory
  • Algorithm for Optimizing MPI Performance
  • Comprehending the Underlying MPI Performance
  • Recalling Some Benchmarking Basics
  • Gauging Default Intranode Communication Performance
  • Gauging Default Internode Communication Performance
  • Discovering Default Process Layout and Pinning Details
  • Gauging Physical Core Performance
  • Doing Initial Performance Analysis
  • Is It Worth the Trouble?
  • Example 1: Initial HPL Performance Investigation
  • Getting an Overview of Scalability and Performance
  • Learning Application Behavior
  • Example 2: MiniFE Performance Investigation
  • Choosing Representative Workload(s)
  • Example 2 (cont.): MiniFE Performance Investigation
  • Balancing Process and Thread Parallelism
  • Example 2 (cont.): MiniFE Performance Investigation
  • Doing a Scalability Review
  • Example 2 (cont.): MiniFE Performance Investigation
  • Analyzing the Details of the Application Behavior
  • Example 2 (cont.): MiniFE Performance Investigation
  • Choosing the Optimization Objective
  • Detecting Load Imbalance
  • Example 2 (cont.): MiniFE Performance Investigation
  • Dealing with Load Imbalance
  • Classifying Load Imbalance
  • Addressing Load Imbalance
  • Example 2 (cont.): MiniFE Performance Investigation
  • Example 3: MiniMD Performance Investigation.
  • Optimizing MPI Performance
  • Classifying the MPI Performance Issues
  • Addressing MPI Performance Issues
  • Mapping Application onto the Platform
  • Understanding Communication Paths
  • Selecting Proper Communication Fabrics
  • Using Scalable Datagrams
  • Specifying a Network Provider
  • Using IP over IB
  • Controlling the Fabric Fallback Mechanism
  • Using Multirail Capabilities
  • Detecting and Classifying Improper Process Layout and Pinning Issues
  • Controlling Process Layout
  • Controlling the Global Process Layout
  • Controlling the Detailed Process Layout
  • Setting the Environment Variables at All Levels
  • Controlling the Process Pinning
  • Controlling Memory and Network Affinity
  • Example 4: MiniMD Performance Investigation on Xeon Phi
  • Example 5: MiniGhost Performance Investigation
  • Tuning the Intel MPI Library
  • Tuning Intel MPI for the Platform
  • Tuning Point-to-Point Settings
  • Adjusting the Eager and Rendezvous Protocol Thresholds
  • Changing DAPL and DAPL UD Eager Protocol Threshold
  • Bypassing Shared Memory for Intranode Communication
  • Bypassing the Cache for Intranode Communication
  • Choosing the Best Collective Algorithms
  • Tuning Intel MPI Library for the Application
  • Using Magical Tips and Tricks
  • Disabling the Dynamic Connection Mode
  • Applying the Wait Mode to Oversubscribed Jobs
  • Fine-Tuning the Message-Passing Progress Engine
  • Reducing the Pre-reserved DAPL Memory Size
  • What Else?
  • Example 5 (cont.): MiniGhost Performance Investigation
  • Optimizing Application for Intel MPI
  • Avoiding MPI_ANY_SOURCE
  • Avoiding Superfluous Synchronization
  • Using Derived Datatypes
  • Using Collective Operations
  • Betting on the Computation/Communication Overlap
  • Replacing Blocking Collective Operations by MPI-3 Nonblocking Ones
  • Using Accelerated MPI File I/O.
  • Example 5 (cont.): MiniGhost Performance Investigation
  • Using Advanced Analysis Techniques
  • Automatically Checking MPI Program Correctness
  • Comparing Application Traces
  • Instrumenting Application Code
  • Correlating MPI and Hardware Events
  • Collecting and Analyzing Hardware Counter Information in ITAC
  • Collecting and Analyzing Hardware Counter Information in VTune
  • Summary
  • References
  • Chapter 6: Addressing Application Bottlenecks: Shared Memory
  • Profiling Your Application
  • Using VTune Amplifier XE for Hotspots Profiling
  • Hotspots for the HPCG Benchmark
  • Compiler-Assisted Loop/Function Profiling
  • Sequential Code and Detecting Load Imbalances
  • Thread Synchronization and Locking
  • Dealing with Memory Locality and NUMA Effects
  • Thread and Process Pinning
  • Controlling OpenMP Thread Placement
  • Thread Placement in Hybrid Applications
  • Summary
  • References
  • Chapter 7: Addressing Application Bottlenecks: Microarchitecture
  • Overview of a Modern Processor Pipeline
  • Pipelined Execution
  • Data Conflicts
  • Control Conflicts
  • Structural Conflicts
  • Out-of-order vs. In-order Execution
  • Superscalar Pipelines
  • SIMD Execution
  • Speculative Execution: Branch Prediction
  • Memory Subsystem
  • Putting It All Together: A Final Look at the Sandy Bridge Pipeline
  • A Top-down Method for Categorizing the Pipeline Performance
  • Intel Composer XE Usage for Microarchitecture Optimizations
  • Basic Compiler Usage and Optimization
  • Using Optimization and Vectorization Reports to Read the Compiler's Mind
  • Optimizing for Vectorization
  • The AVX Instruction Set
  • Why Doesn't My Code Vectorize in the First Place?
  • Data Dependences
  • Data Aliasing
  • Array Notations
  • Vectorization Directives
  • ivdep
  • vector
  • simd
  • Understanding AVX: Intrinsic Programming
  • What Are Intrinsics?.
  • First Steps: Loading and Storing
  • Arithmetic
  • Data Rearrangement
  • Dealing with Disambiguation
  • Dealing with Branches
  • __builtin_expect
  • Profile-Guided Optimization
  • Pragmas for Unrolling Loops and Inlining
  • unroll/nounroll
  • unroll_and_jam/nounroll_and_jam
  • inline, noinline, forceinline
  • Specialized Routines: How to Exploit the Branch Prediction for Maximal Performance
  • When Optimization Leads to Wrong Results
  • Using a Standard Library Method
  • Using a Manual Implementation in C
  • Vectorization with Directives
  • Analyzing Pipeline Performance with Intel VTune Amplifier XE
  • Summary
  • References
  • Chapter 8: Application Design Considerations
  • Abstraction and Generalization of the Platform Architecture
  • Types of Abstractions
  • Levels of Abstraction and Complexities
  • Raw Hardware vs. Virtualized Hardware in the Cloud
  • Questions about Application Design
  • Designing for Performance and Scaling
  • Designing for Flexibility and Performance Portability
  • Data Layout
  • Structured Approach to Express Parallelism
  • Understanding Bounds and Projecting Bottlenecks
  • Data Storage or Transfer vs. Recalculation
  • Total Productivity Assessment
  • Summary
  • References
  • Index.

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