Concepts and Terminology Parallel Computer Memory Architectures
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Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Hybrid Distributed-Shared Memory Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Comparison of Shared and Distributed Memory Architectures Architecture CC-UMA
CC-NUMA Distributed Examples SMPs,
DEC/Compaq, SGI Challenge, IBM POWER3 SGI
Origin, Sequent, IBM POWER4 (MCM), DEC/Compaq Cray T3E, Mas- par, IBM SP2 CommunicationsMPI, Threads, OpenMP,
shmem MPI, Threads, OpenMP, shmem
MPI Scalability to 10s of proc. to 100s of proc. to 1000s of proc. Draw Backs Memory-CPU bandwidth Memory-CPU bandwidth, Non-uniform access times System adm., Programming is hard to develop and maintain Software
Availability many
1000s ISVs
many 1000s
ISVs 100s ISVs Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Hybrid Distributed-Shared Memory (...) The largest and fastest computers in the world today employ both shared and distributed memory architectures. The shared memory component is usually a cache coherent SMP machine. Processors on a given SMP can address that machine's memory as global. The distributed memory component is the networking of multiple SMPs. SMPs know only about their own memory - not the memory on another SMP. Therefore, network communications are required to move data from one SMP to another.
Current trends seem to indicate that this type of memory architecture will continue to prevail and increase at the high end of computing for the foreseeable future. Advantages and Disadvantages: whatever is common to both shared and distributed memory architectures. Blaise Barney, Livermore Computing Introduction to Parallel Computing
Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Overview
There are several parallel programming models in common use: Shared Memory Threads Message Passing Data Parallel Hybrid
Parallel programming models exist as an abstraction above hardware and memory architectures. Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs These models are NOT speci c to a particular type of machine or memory architecture. In fact, these models can (theoretically) be implemented on any underlying hardware. Two examples: 1 Shared memory model on a distributed memory machine: Kendall Square Research (KSR) ALLCACHE approach. Machine memory was physically distributed, but appeared to the user as a single shared memory (global address space). Generically, this approach is referred to as "virtual shared memory". 2 Message passing model on a shared memory machine: MPI on SGI Origin. The SGI Origin employed the CC-NUMA type of shared memory architecture, where every task has direct access to global memory. However, the ability to send and receive messages with MPI, as is commonly done over a network of distributed memory machines, is is very commonly used. Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Which model to use is often a combination of what is available and personal choice. There is no "best" model, although there certainly are better implementations of some models over others. Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Shared Memory Model In the shared-memory programming model, tasks share a common address space, which they read and write asynchronously. Various mechanisms such as locks / semaphores may be used to control access to the shared memory. An advantage of this model from the programmer's point of view is that the notion of data "ownership" is lacking, so there is no need to specify explicitly the communication of data between tasks. Program development can often be simpli ed. An important disadvantage in terms of performance is that it becomes more di cult to understand and manage data locality. Blaise Barney, Livermore Computing Introduction to Parallel Computing
Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Implementations On shared memory platforms, the native compilers translate user program variables into actual memory addresses, which are global. No common distributed memory platform implementations currently exist. However, as mentioned previously in the Overview section, the KSR ALLCACHE approach provided a shared memory view of data even though the physical memory of the machine was distributed. Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Threads Model In the threads model of parallel programming, a single process can have multiple, concurrent execution paths. An analogy to describe threads is the concept of a single program that includes a number of subroutines. Blaise Barney, Livermore Computing Introduction to Parallel Computing Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs The main program a.out is scheduled to run by the native OS. It performs some serial work, and then creates tasks (threads) that can be scheduled and run by the OS concurrently. Each thread has local data, but also, shares the entire resources of a.out. Each thread also bene ts from a global memory view because it shares the memory space of a.out. A thread's work may best be described as a subroutine within the main program. Any thread can execute any subroutine at the same time as other threads. Threads communicate with each other through global memory This requires synchronization constructs to insure that more than one thread is not updating the same global address at any time. Threads can come and go, but a.out remains present to provide the necessary shared resources until the application has completed. Blaise Barney, Livermore Computing Introduction to Parallel Computing
Overview Concepts and Terminology Parallel Computer Memory Architectures Parallel Programming Models Designing Parallel Programs Threads are commonly associated with shared memory architectures and operating systems. Blaise Barney, Livermore Computing Introduction to Parallel Computing Yüklə 152,39 Kb. Dostları ilə paylaş:
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