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Q. Instruction per cycle in RISC?
One instruction per cycle: A machine cycle is total time taken to fetch two operands from registers perform ALU operation on them and store result in a register. So RISC instruction execution takes about same time as micro-instructions on CISC machines. With these simple instruction execution instead of micro-instructions, it can use fast logic circuits for control unit, so increasing execution efficiency further.
Granularity Granularity refers to the quantity of computation done in parallel relative to the dimension of the entire program. In parallel computing, granularity is a qualitat
In this task you are supposed to create three UML diagrams. The conditions are given by the scenario in the document Theatre Case (on Blackboard). A theatre manager has ordered a s
Explain how a node can be inserted into an AVL tree. We can insert a node into an AVL tree through the insertion algorithm for binary search trees in which we compare the key o
In a DTMF phone, digits are represented by: (A) Orthogonal frequencies. (B) Orthogonal Phases. (C) Orthogonal codes. (D) Orthogonal pulses. Ans: Di
Program testing and debugging: Program testing is the method of checking program, to verify that it satisfies its needs and to detect errors. These errors can be of any type-
Q. Combined Parallel Work-sharing Constructs? Combined parallel work sharing constructs are shortcuts for specifying a work sharing construct nested instantaneously in a parall
Bernstein Conditions for Detection of Parallelism For execution of a number of instructions or a block of instructions in parallel, it must be made certain that instructions ar
Design a 1-bit full adder: Verify your design Use the 1-bit full adder to build a 4-bit adder with Ci=0 Verify: 1 + 4, and 9 + 9 Sram design: Cell: p - 0.5/0.045;
What are the Requirements to design Sequential circuit Ans . Design Requirements of Sequential circuit: (i) The circuit specifications translated into a state diagram
Avoiding Overfitting : However remember there that in the previous lecture, there is over fitting that common problem in machine learning. Furthermore details to decision tree
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