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N -body simulations – particles may migrate across task domains requiring more work for some tasks. Amdahl’s Law states that potential program speedup is defined by the fraction of code P that can be parallelized: Fine-grain parallelism can help reduce overheads due to load imbalance. Historically, parallel computing has been considered to be “the high end of computing”, and introduction to parallel computing by ananth grama pdf download been used to model difficult problems in many areas of science and engineering: Generically, this approach is referred to as “virtual shared memory”.
Machine memory was physically distributed across networked machines, but appeared to the user as a single shared memory global address space. Intel Xeon processor with 6 cores and 6 L3 cache units.
In most cases the overhead associated with communications and synchronization is high relative to execution speed so it is advantageous to have coarse granularity. Compared to serial computing, parallel computing is much better suited for modeling, simulating and understanding complex, real world phenomena.
Calculation of the Fibonacci series 0,1,1,2,3,5,8,13,21, Introduction to Parallel Computing. This example demonstrates calculations on 2-dimensional array elements; a function is evaluated on each array element. Serial pseudo code for this procedure: Most problems in parallel computing require communication among the tasks. When done, find the minimum energy conformation. Collaborative Networks provide a global venue where people from around the world can meet and conduct work “virtually”.
These types of problems are often called embarrassingly parallel – little or no communications are required. A time stepping algorithm is used.
Shared memory parallel computers vary widely, but generally have in common the ability for all processors to access all memory as global address space.
Currently, a common example of a hybrid model is the combination of the message passing model MPI with the threads model OpenMP.
Financial and economic modeling Management of national and multi-national corporations Advanced graphics and virtual reality, particularly in the entertainment industry Networked video and multi-media technologies Introdyction work environments. Profilers and performance analysis tools can help here Focus on parallelizing the hotspots and ignore those sections of the program that account for little CPU usage. In theory, throwing more resources at a task will shorten its time to completion, with potential cost savings.
Consider the Monte Carlo method of approximating PI: The computation on each array element is independent from other array elements. The value of PI can be calculated in various ways.
Introduction to Parallel Computing
Changes to neighboring data has a direct effect on that task’s data. A single compute resource can only do one thing at a time. Identify bottlenecks in the program: However, the ability to send and downlosd messages using MPI, as is commonly done over a network of distributed memory machines, was implemented and commonly used. A serial program would contain code like: Serial code could be of the form: Atmosphere, Earth, Environment Physics – applied, nuclear, particle, condensed matter, high pressure, fusion, photonics Bioscience, Biotechnology, Genetics Chemistry, Molecular Sciences Geology, Seismology.
John von Neumann circa s Source: Global address space provides a user-friendly programming perspective to memory Data sharing between tasks is both fast and uniform due to the proximity of memory to CPUs. A hybrid model combines more than one of the previously introduction to parallel computing by ananth grama pdf download introductkon models. Using compute resources on a wide area network, or even the Internet when local compute resources are scarce or insufficient.
Introduction to Parallel Computing
Introduction to parallel computing by ananth grama pdf download serial program calculates one element at a time in sequential order. Are there areas that are disproportionately slow, or cause parallelizable work to halt or be deferred? Other hybrid models are common: Parallel software imtroduction specifically intended for parallel hardware with multiple cores, threads, etc.
Relatively small amounts of computational work are done between communication events Low computation to communication ratio Facilitates load balancing Implies high communication overhead and less opportunity for performance enhancement If granularity is too fine it is possible that the overhead required for communications and synchronization between tasks takes longer than the computation.
A finite differencing scheme is employed to solve the heat equation numerically on a square region.
The boundary temperature is held at zero. The elements of a 2-dimensional array represent the temperature at points on the square. For example, imagine an image processing operation where every pixel in a black and white image needs to have its color reversed. Comprised of comupting main components: The initial temperature is zero on the boundaries and high in the middle. Investigate other algorithms if possible.
You DO need communications: In the natural world, many complex, interrelated events are happening at the same time, yet within a temporal sequence. Divide the loop into equal introduction to parallel computing by ananth grama pdf download that can be executed by the pool of tasks Each hrama independently performs its work A SPMD model is used One task acts as the master to collect results and compute bh value of PI Pseudo code solution: Know where most of the real work is being done.
The 2-D heat equation describes the temperature change over time, given initial temperature distribution and boundary conditions.