|
Speedup
In computer architecture, speedup is a number that measures the relative performance of two systems processing the same problem. More technically, it is the improvement in speed of execution of a task executed on two similar architectures with different resources. The notion of speedup was established by Amdahl's law, which was particularly focused on parallel processing. However, speedup can be used more generally to show the effect on performance after any resource enhancement. Definitions Speedup can be defined for two different types of quantities: '' latency'' and ''throughput''. ''Latency'' of an architecture is the reciprocal of the execution speed of a task: : L = \frac = \frac, where * ''v'' is the execution speed of the task; * ''T'' is the execution time of the task; * ''W'' is the execution workload of the task. ''Throughput'' of an architecture is the execution rate of a task: : Q = \rho vA = \frac = \frac, where * ''ρ'' is the execution density (e.g., the numbe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Amdahl's Law
In computer architecture, Amdahl's law (or Amdahl's argument) is a formula that shows how much faster a task can be completed when more resources are added to the system. The law can be stated as: "the overall performance improvement gained by optimizing a single part of a system is limited by the fraction of time that the improved part is actually used". It is named after computer scientist Gene Amdahl, and was presented at the American Federation of Information Processing Societies (AFIPS) Spring Joint Computer Conference in 1967. Amdahl's law is often used in parallel computing to predict the theoretical speedup when using multiple processors. Definition In the context of Amdahl's law, speedup can be defined as: \text = \frac or \text = \frac Amdahl's law can be formulated in the following way: : \text_\text = \frac where * \text_\text represents the total speedup of a program * \text_ represents the proportion of time spent on the portion of the code where improve ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel Computing
Parallel computing is a type of computing, computation in which many calculations or Process (computing), processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: Bit-level parallelism, bit-level, Instruction-level parallelism, instruction-level, Data parallelism, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance inc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gustafson's Law
In computer architecture, Gustafson's law (or Gustafson–Barsis's law) gives the speedup in the execution time of a task that theoretically gains from parallel computing, using a hypothetical run of ''the task'' on a single-core machine as the baseline. To put it another way, it is the theoretical "slowdown" of an ''already parallelized'' task if running on a serial machine. It is named after computer scientist John L. Gustafson and his colleague Edwin H. Barsis, and was presented in the article ''Reevaluating Amdahl's Law'' in 1988. Definition Gustafson estimated the speedup S of a program gained by using parallel computing as follows: \begin S &= s + p \times N \\ &= s + (1 - s) \times N \\ &= N + (1 - N) \times s \end where * S is the theoretical speedup of the program with parallelism (scaled speedup); * N is the number of processors; * s and p are the fractions of time spent executing the serial parts and the parallel parts of the program, respectively, on the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Karp–Flatt Metric
The Karp–Flatt metric is a measure of parallelization of code in parallel processor systems. This metric exists in addition to Amdahl's law and Gustafson's law as an indication of the extent to which a particular computer code is parallelized. It was proposed by Alan H. Karp and Horace P. Flatt in 1990. Description Given a parallel computation exhibiting speedup \psi on p processors, where p > 1, the experimentally determined serial fraction e is defined to be the Karp–Flatt Metric viz: :e = \frac The lower the value of e, the better the parallelization. Justification There are many ways to measure the performance of a parallel algorithm running on a parallel processor. The Karp–Flatt metric defines a metric which reveals aspects of the performance that are not easily discerned from other metrics. A pseudo-"derivation" of sorts follows from Amdahl's Law, which can be written as: :T(p) = T_s + \frac Where: *T(p) is the total time taken for code execution in a p-processo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BLAST (biotechnology)
In bioinformatics, BLAST (basic local alignment search tool) is an algorithm and program for comparing Primary structure, primary biological sequence information, such as the amino acid, amino-acid sequences of proteins or the nucleotides of DNA sequence, DNA and/or RNA sequences. A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query) with a library or database of sequences, and identify database sequences that resemble the query sequence above a certain threshold. For example, following the discovery of a previously unknown gene in the Mus musculus, mouse, a scientist will typically perform a BLAST search of the human genome to see if humans carry a similar gene; BLAST will identify sequences in the human genome that resemble the mouse gene based on similarity of sequence. Background BLAST is one of the most widely used bioinformatics programs for sequence searching. It addresses a fundamental problem in bioinformatics research ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Scalability
Scalability is the property of a system to handle a growing amount of work. One definition for software systems specifies that this may be done by adding resources to the system. In an economic context, a scalable business model implies that a company can increase sales given increased resources. For example, a package delivery system is scalable because more packages can be delivered by adding more delivery vehicles. However, if all packages had to first pass through a single warehouse for sorting, the system would not be as scalable, because one warehouse can handle only a limited number of packages. In computing, scalability is a characteristic of computers, networks, algorithms, networking protocols, programs and applications. An example is a search engine, which must support increasing numbers of users, and the number of topics it indexes. Webscale is a computer architectural approach that brings the capabilities of large-scale cloud computing companies into enterprise ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel Slowdown
Parallel slowdown is a phenomenon in parallel computing where parallelization of a parallel algorithm In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract mach ... beyond a certain point causes the program to run slower (take more time to run to completion). Parallel slowdown is typically the result of a communications bottleneck. As more processor nodes are added, each processing node spends progressively more time doing communication than useful processing. At some point, the communications overhead created by adding another processing node surpasses the increased processing power that node provides, and parallel slowdown occurs. Parallel slowdown occurs when the algorithm requires significant communication, particularly of intermediate results. Some problems, known as embarrassingly p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CPU Cache
A CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations. Most CPUs have a hierarchy of multiple cache levels (L1, L2, often L3, and rarely even L4), with different instruction-specific and data-specific caches at level 1. The cache memory is typically implemented with static random-access memory (SRAM), in modern CPUs by far the largest part of them by chip area, but SRAM is not always used for all levels (of I- or D-cache), or even any level, sometimes some latter or all levels are implemented with eDRAM. Other types of caches exist (that are not counted towards the "cache size" of the most important caches mentioned above), such as the translation lookaside buffer (TLB) which is part of the memory management unit (M ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brooks's Law
Brooks's law is an observation about software project management that "Adding manpower to a late software project makes it later."Frederick P. Brooks, Jr. ''The Mythical Man-Month''. 1995 975 Addison-Wesley. It was coined by Fred Brooks in his 1975 book ''The Mythical Man-Month''. According to Brooks, under certain conditions, an incremental person when added to a project makes it take more, not less time. Explanations According to Brooks himself, the law is an "outrageous oversimplification", but it captures the general rule. Brooks points to the main factors that explain why it works this way: # It takes some time for the people added to a project to become productive. Brooks calls this the " ramp up" time. Software projects are complex engineering endeavors, and new workers on the project must first become educated about the work that has preceded them; this education requires diverting resources already working on the project, temporarily diminishing their productivity while ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Backtracking
Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it determines that the candidate cannot possibly be completed to a valid solution. The classic textbook example of the use of backtracking is the eight queens puzzle, that asks for all arrangements of eight chess queens on a standard chessboard so that no queen attacks any other. In the common backtracking approach, the partial candidates are arrangements of ''k'' queens in the first ''k'' rows of the board, all in different rows and columns. Any partial solution that contains two mutually attacking queens can be abandoned. Backtracking can be applied only for problems which admit the concept of a "partial candidate solution" and a relatively quick test of whether it can possibly be completed to a valid solution. It is useless, for exampl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
