Distributed Memory
General Characteristics:
Like shared memory systems, distributed memory systems vary widely but share a common characteristic.
Distributed memory systems require a communication network to connect inter-processor memory.
Processors have their own local memory. Memory addresses in one processor do not map to another processor, so there is no concept of global address space across all processors.
Because each processor has its own local memory, it operates independently. Changes it makes to its local memory have no effect on the memory of other processors. Hence, the concept of cache coherency does not apply.
When a processor needs access to data in another processor, it is usually the task of the programmer to explicitly define how and when data is communicated. Synchronization between tasks is likewise the programmer's responsibility.
The network "fabric" used for data transfer varies widely, though it can can be as simple as Ethernet.
Advantages:
Memory is scalable with number of processors. Increase the number of processors and the size of memory increases proportionately.
Each processor can rapidly access its own memory without interference and without the overhead incurred with trying to maintain cache coherency.
Cost effectiveness: can use commodity, off-the-shelf processors and networking.
Disadvantages:
The programmer is responsible for many of the details associated with data communication between processors.
It may be difficult to map existing data structures, based on global memory, to this memory organization.
Non-uniform memory access (NUMA) times
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.
Message Passing Model
The message passing model demonstrates the following characteristics:# A set of tasks that use their own local memory during computation. Multiple tasks can reside on the same physical machine and/or across an arbitrary number of machines.
# Tasks exchange data through communications by sending and receiving messages.
# Data transfer usually requires cooperative operations to be performed by each process. For example, a send operation must have a matching receive operation.
Models
There are several parallel programming models in common use:
o Shared Memory
o Threads
o Message Passing
o Data Parallel
o Hybrid
Parallel programming models exist as an abstraction above hardware and memory architectures.
Although it might not seem apparent, these models are NOT specific to a particular type of machine or memory architecture. In fact, any of these models can (theoretically) be implemented on any underlying hardware. Two examples:
1st Model
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". Note: although KSR is no longer in business, there is no reason to suggest that a similar implementation will not be made available by another vendor in the future.
2nd Model
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 not only implemented but is very commonly used.
* 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.
* The following sections describe each of the models mentioned above, and also discuss some of their actual implementations.