Appendix A : Terminology (taken from the Beowulf-HOWTO)

Although parallel processing has been used for many years in many systems, it is still somewhat unfamiliar to most computer users. Thus, before discussing the various alternatives, it is important to become familiar with a few commonly used terms.

SIMD

SIMD (Single Instruction stream, Multiple Data stream) refers to a parallel execution model in which all processors execute the same operation at the same time, but each processor is allowed to operate upon its own data. This model naturally fits the concept of performing the same operation on every element of an array, and is thus often associated with vector or array manipulation. Because all operations are inherently synchronized, interactions among SIMD processors tend to be easily and efficiently implemented.

MIMD

MIMD (Multiple Instruction stream, Multiple Data stream) refers to a parallel execution model in which each processor is essentially acting independently. This model most naturally fits the concept of decomposing a program for parallel execution on a functional basis; for example, one processor might update a database file while another processor generates a graphic display of the new entry. This is a more flexible model than SIMD execution, but it is achieved at the risk of debugging nightmares called race conditions, in which a program may intermittently fail due to timing variations reordering the operations of one processor relative to those of another.

SPMD

SPMD (Single Program, Multiple Data) is a restricted version of MIMD in which all processors are running the same program. Unlike SIMD, each processor executing SPMD code may take a different control flow path through the program.

Communication Bandwidth

The bandwidth of a communication system is the maximum amount of data that can be transmitted in a unit of time... once data transmission has begun. Bandwidth for serial connections is often measured in baud or bits/second (b/s), which generally correspond to 1/10 to 1/8 that many Bytes/second (B/s). For example, a 1,200 baud modem transfers about 120 B/s, whereas a 155 Mb/s ATM network connection is nearly 130,000 times faster, transferring about about 17 MB/s. High bandwidth allows large blocks of data to be transferred efficiently between processors.

Communication Latency

The latency of a communication system is the minimum time taken to transmit one object, including any send and receive software overhead. Latency is very important in parallel processing because it determines the minimum useful grain/block size, the minimum run time for a segment of code to yield speed-up through parallel execution. Basically, if a segment of code runs for less time than it takes to transmit its result value (i.e., latency), executing that code segment serially on the processor that needed the result value would be faster than parallel execution; serial execution would avoid the communication overhead.

Message Passing

Message passing is a model for interactions between processors within a parallel system. In general, a message is constructed by software on one processor and is sent through an interconnection network to another processor, which then must accept and act upon the message contents. Although the overhead in handling each message (latency) may be high, there are typically few restrictions on how much information each message may contain. Thus, message passing can yield high bandwidth making it a very effective way to transmit a large block of data from one processor to another. However, to minimize the need for expensive message passing operations, data structures within a parallel program must be spread across the processors so that most data referenced by each processor is in its local memory... this task is known as data layout.

Shared Memory

Shared memory is a model for interactions between processors within a parallel system. Systems like the multi-processor Pentium machines running Linux physically share a single memory among their processors, so that a value written to shared memory by one processor can be directly accessed by any processor. Alternatively, logically shared memory can be implemented for systems in which each processor has it own memory by converting each non-local memory reference into an appropriate inter-processor communication. Either implementation of shared memory is generally considered easier to use than message passing. Physically shared memory can have both high bandwidth and low latency, but only when multiple processors do not try to access the bus simultaneously; thus, data layout still can seriously impact performance, and cache effects, etc., can make it difficult to determine what the best layout is.

Aggregate Functions

In both the message passing and shared memory models, a communication is initiated by a single processor; in contrast, aggregate function communication is an inherently parallel communication model in which an entire group of processors act together. The simplest such action is a barrier synchronization, in which each individual processor waits until every processor in the group has arrived at the barrier. By having each processor output a datum as a side-effect of reaching a barrier, it is possible to have the communication hardware return a value to each processor which is an arbitrary function of the values collected from all processors. For example, the return value might be the answer to the question "did any processor find a solution?" or it might be the sum of one value from each processor. Latency can be very low, but bandwidth per processor also tends to be low. Traditionally, this model is used primarily to control parallel execution rather than to distribute data values.

Collective Communication

This is another name for aggregate functions, most often used when referring to aggregate functions that are constructed using multiple message-passing operations.

SMP

SMP (Symmetric Multi-Processor) refers to the operating system concept of a group of processors working together as peers, so that any piece of work could be done equally well by any processor. Typically, SMP implies the combination of MIMD and shared memory. In the IA32 world, SMP generally means compliant with MPS (the Intel MultiProcessor Specification); in the future, it may mean "Slot 2".

SWAR

SWAR (SIMD Within A Register) is a generic term for the concept of partitioning a register into multiple integer fields and using register-width operations to perform SIMD-parallel computations across those fields. Given a machine with k-bit registers, data paths, and function units, it has long been known that ordinary register operations can function as SIMD parallel operations on as many as n, k/n-bit, field values. Although this type of parallelism can be implemented using ordinary integer registers and instructions, many high-end microprocessors have recently added specialized instructions to enhance the performance of this technique for multimedia-oriented tasks. In addition to the Intel/AMD/Cyrix MMX (MultiMedia eXtensions), there are: Digital Alpha MAX (MultimediA eXtensions), Hewlett-Packard PA-RISC MAX (Multimedia Acceleration eXtensions), MIPS MDMX (Digital Media eXtension, pronounced "Mad Max"), and Sun SPARC V9 VIS (Visual Instruction Set). Aside from the three vendors who have agreed on MMX, all of these instruction set extensions are roughly comparable, but mutually incompatible.

Attached Processors

Attached processors are essentially special-purpose computers that are connected to a host system to accelerate specific types of computation. For example, many video and audio cards for PCs contain attached processors designed, respectively, to accelerate common graphics operations and audio DSP (Digital Signal Processing). There is also a wide range of attached array processors, so called because they are designed to accelerate arithmetic operations on arrays. In fact, many commercial supercomputers are really attached processors with workstation hosts.

RAID

RAID (Redundant Array of Inexpensive Disks) is a simple technology for increasing both the bandwidth and reliability of disk I/O. Although there are many different variations, all have two key concepts in common. First, each data block is striped across a group of n+k disk drives such that each drive only has to read or write 1/n of the data... yielding n times the bandwidth of one drive. Second, redundant data is written so that data can be recovered if a disk drive fails; this is important because otherwise if any one of the n+k drives were to fail, the entire file system could be lost. A good overview of RAID in general is given at <http://www.dpt.com/uraiddoc.html>, and information about RAID options for Linux systems is at <http://linas.org/linux/raid.html>. Aside from specialized RAID hardware support, Linux also supports software RAID 0, 1, 4, and 5 across multiple disks hosted by a single Linux system; see the Software RAID mini-HOWTO and the Multi-Disk System Tuning mini-HOWTO for details. RAID across disk drives on multiple machines in a cluster is not directly supported.

IA32

IA32 (Intel Architecture, 32-bit) really has nothing to do with parallel processing, but rather refers to the class of processors whose instruction sets are generally compatible with that of the Intel 386. Basically, any Intel x86 processor after the 286 is compatible with the 32-bit flat memory model that characterizes IA32. AMD and Cyrix also make a multitude of IA32-compatible processors. Because Linux evolved primarily on IA32 processors and that is where the commodity market is centered, it is convenient to use IA32 to distinguish any of these processors from the PowerPC, Alpha, PA-RISC, MIPS, SPARC, etc. The upcoming IA64 (64-bit with EPIC, Explicitly Parallel Instruction Computing) will certainly complicate matters, but Merced, the first IA64 processor, is not scheduled for production until late 1999.

COTS