PARALLEL ARCHITECTURAL LANDSCAPE
Parallel Computing, in its basic sense, is multiple operations being carried out simultaneously, that is, a problem can be divided into sub problems which can be solved concurrently. Throughout the history, attempts have been made and have been successful to increase the degree of parallelism in computing as much as possible. During this course, many restrictions have been encountered and alongside the possible solutions were suggested by the brightest minds. Parallelism can be divided in many ways:
1. Fine-Grained Parallelism – When the processors must communicate with each other many times per second.
Coarse-Grained Parallelism – When the processors communicate with each other once every few seconds.
2. Bit-Level Parallelism – When the number of operations to be performed are reduced by increasing the word size. The first processor launched by Intel in 1970s was 4-bit and the systems that we work on today are mostly 64-bit. This was the main source of speed-up till the mid 1980s.
Instruction-Level Parallelism - When instructions are combined into groups and then executed in parallel. Modern processors have pipelining in which each stage performs a different instruction.
FLYNN’S TAXONOMY
Single instruction Multiple instruction
Single data SISD
MISD
Multiple data SIMD
MIMD
1. SISD : Single Instruction-Single Data
This is the simplest kind of architecture. This is equivalent to an entirely sequential program and hardly employs any parallelism.
2. MISD : Multiple Instruction-Single Data
No significant applications apart from systolic arrays have been devised for this kind of architecture and therefore this classification is rarely used.
3. SIMD : Single Instruction-Multip...
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... model cannot be extended beyond 32 processors.
Parallel Computing in Future
In my opinion, the major potential in parallel computing lies in the software part. Hardware architectures have been constantly evolving since the last 40 years and sooner or later saturation may start. The number of transistors cannot keep increasing forever. Even though software has evolved, it’s still not up to pace. There is a dearth of programmers trained to design and program parallel systems. Intel recently launched Parallel Computing Center program with the main purpose as “keeping the parallel software in sync with the parallel hardware”. The international community needs to develop the parallel programming skills to keep pace with the new processors being created. As this realization spreads, the parallel architectural landscape will touch even greater heights than expected.
rapidly chooses how to convey the set of uses and framework servers over different machines in the cloud. Large portions of the conventional parallel applications for the most part utilize an altered number of strings on the other hand procedures characterized as a parameter toward the begin of the application. The choice for the number of strings is frequently chosen by the client in a push to completely use the parallel assets of the framework or to take care of top demand of a specific administration. fos utilizes the duplicated server model which permits extra transforming units to be alterably included amid runtime permitting the framework to attain a finer use for element workloads and lightening the client from such
If you are one of the people who are not convinced by multi-core processors and are adamant that no program needs more than two cores, then you should stop reading right about now. However if you’re one that embraces technology, be it beneficial now or in the future, 2010 has to be one of the best years in CPU technology in a long time. AMD and Intel have both introduced six core CPUs and both of them have been met with some excitement, rightfully so because six cores are really better than four.
“After the integrated circuits the only place to go was down—in size that it. Large scale integration (LS) could fit hundreds of components onto one chip. By the 1980’s, very large scale integration (VLSI) squeezed hundreds of thousands of components onto a chip. Ultra-Large scale integration (ULSI) increased that number into millions. The ability to fit so much onto an area about half the size of ...
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A port is a point at which you can attach leads from devices to the
In the past few decades, one field of engineering in particular has stood out in terms of development and commercialisation; and that is electronics and computation. In 1965, when Moore’s Law was first established (Gordon E. Moore, 1965: "Cramming more components onto integrated circuits"), it was stated that the number of transistors (an electronic component according to which the processing and memory capabilities of a microchip is measured) would double every 2 years. This prediction held true even when man ushered in the new millennium. We have gone from computers that could perform one calculation in one second to a super-computer (the one at Oak Ridge National Lab) that can perform 1 quadrillion (1015) mathematical calculations per second. Thus, it is only obvious that this field would also have s...
... SoC, such as processors, memories, accelerators, and peripherals. This architectural model is often referred as parallel architecture model.
The Von Neumann bottleneck is a limitation on material or data caused by the standard personal computer architecture. Earlier computers were fed programs and data for processing while they were running. Von Neumann created the idea behind the stored program computer, our current standard model. In the Von Neumann architecture, programs and data are detained or held in memory, the processor and memory are separate consequently data moves between the two. In that configuration, latency or dormancy is unavoidable. In recent years, processor speeds have increased considerably. Memory enhancements, in contrast, have mostly been in size or volume. This enhancement gives it the ability to store more data in less space; instead of focusing on transfer rates. As the speeds have increased, the processors now have spent an increasing amount of time idle, waiting for data to be fetched from the memory. All in all, No matter how fast or powerful a...
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