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What is Random access memory (RAM)
This is a volatile memory (i.e. contents are lost when computer is switched off). A user can write or delete data and read the contents. Before a program can be ran it should first be loaded into RAM that allows CPU to access the program. Battery-backed RAMs overcome data loss on switching power off though are outside the scope of these booklets.
(NOTE: For completeness, it's worth mentioning that two types of RAM exist termed as SRAM (static RAM) and DRAM (dynamic RAM) - SRAM doesn't need to be constantly refreshed to retain its memory unlike DRAM. Also consider that computers use cache which is a part of memory made from SRAM. Memory caching works as programs generally access the same data or instructions over and over again. By retaining as much information as possible in SRAM, computer operates more quickly (cache is generally termed level 1, 2 or 3 (termed L1, L2 or L3)).
What is the max no of match code Id's that can be defined for one Match code object? A match code Id is a single character ID that can be a letter or a number.
explain in RAID
What is write-back or copy-back protocol? For a write operation using this protocol during write-hit: the method is to update only the cache and to mark it as updated with an a
Features of MPI-1 Binding for FORTRAN and C Collective communication Communication domains and Process groups Point-to-point communication Virtual process
How do we merge an image from a file to the current image in GIMP? Ans) Use "File then Open as Layers" menu command or just take the file to a window and drop it there. The file w
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We are planning an orienteering game. The aim of this game is to arrive at the goal (G) from the start (S) with the shortest distance. However, the players have to pass all the che
Evaluate x = A ‾.B + C ( ) using the convention A = True and B = False. Ans. Simplify given expression x = A ‾ .B + C ( ) as = A ‾ B + C (A ‾ + D ‾ ) (As = A ‾ +D ‾ usin
output devices used in virtual rality
Learning Weights in Perceptrons In detail we will look at the learning method for weights in multi-layer networks next chapter. The following description of learning in percept
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