Monday, October 18, 2010

MPI Programming Exam Questions

Feel free to give answers to unanswered questions as comments


1.  Sum of prime factors :

http://people.sc.fsu.edu/%7Ejburkardt/presentations/fdi_2008_lecture8.pdf#page=16

Add up the prime numbers from 2 to N.
Each of P processors will simply take about 1/P of the range of
numbers to check, and add up the primes locally.
When it's done, it will send the partial result to processor 0.

2.  Deadlock avoidance when using blocking send and receive in order.

http://www.cs.ucsb.edu/~hnielsen/cs140/mpi-deadlocks.html


  1.  In MPI, when does a non-blocking recv message return?
          
  1.  What is an MPI communicator?   What is MPI_COMM_WORLD?
            Two processors must be in a common "communicator group" in order to communicate. This is simply  a way for the user to organize  processors into sub-groups. All processors can communicate in the
shared group known as MPI_COMM_WORLD.
  1.  In MPI, what is a process rank?
          
  1.  True or false:  In MPI you set the number of processes when you write the source code.
           No. Number of processes are given on execution.
  1.  Give a short piece of pseudocode that illustrates the master/slave programming model.

  1.  Explain if the following MPI code segment is correct or not, and why:
    Process 0 executes:
MPI_Recv(&yourdata, 1, MPI_FLOAT, 1, tag, MPI_COMM_WORLD, &status);
MPI_Send(&mydata, 1, MPI_FLOAT, 1, tag, MPI_COMM_WORLD);
Process 1 executes:
MPI_Recv(&yourdata, 1, MPI_FLOAT, 0, tag,MPI_COMM_WORLD, &status);
MPI_Send(&mydata, 1, MPI_FLOAT, 0, tag, MPI_COMM_WORLD);

Both are blocking receives waiting for each other to send. System is deadlocked.

  1.  Suppose that process 0 has variable A, and process 1 also has a variable A. Write MPI-like pseudocode to exchange these values between the processes.
          P0:
          send(P1,A)
          recieve(P0,A)

          P1:
          recieve(P1,A)
          send(P0,A)


  1.  Explain the purpose of each of the library calls listed.
·         MPI_Init
·         MPI_Finalize
·         MPI_Comm_rank
·         MPI_Comm_size
·         MPI_Send
·         MPI_Recv
·         MPI_Barrier
·         MPI_Bcast
·         MPI_Scatter
·         MPI_Gather
·         MPI_Reduce
  1.  What is an MPI derived datatype and when would you use one?  Give an example. 
  2. Derived datatypes are datatypes that are built from the basic MPI datatypes.
  3. In MPI, when does a blocking recv message return?
               Blocks until it receives message
  4. True or false:  You can write a program using MPI that will run across all of the cores of your multicore computer in parallel.  Also, if this is possible, indicate if you think this is a good way to write the program.  You must justify your answer to receive credit.  
  5. Discuss marshalling in MPI.
  6. http://books.google.com/books?id=LLdekoUxmr0C&pg=PA86&lpg=PA86&dq=MPI+marshalling&source=bl&ots=aLn5ivDP2i&sig=ElkL0CwR55hVES-tQJjoAKBIIaI&hl=en&ei=U3nITNq7NYrAsAPqytW9DQ&sa=X&oi=book_result&ct=result&resnum=10&ved=0CE0Q6AEwCQ#v=onepage&q=MPI%20marshalling&f=false
  7. When does a blocking send return.
           MPI uses buffering by default. Send returns when message is saved in receivers buffer. Process calling  MPI_Send can continue even if destination has not received the message.

16. Programming question 1 : http://www.cs.usfca.edu/~peter/cs220/mt1_old_key#page=6.pdf
17.  Programming question2 :  http://www.cs.usfca.edu/~peter/cs220/mt1_key#page=4.pdf









    Wednesday, September 29, 2010

    Memory management questions

    Assume you have a small virtual address space of size 64 KB. Further assume that this is a system
    that uses paging and that each page is of size 8 KB.
    (a) How many bits are in a virtual address in this system?

    16 (1-KB of address space needs 10 bits, and 64 needs 6; thus 16).

    (b) Recall that with paging, a virtual address is usually split into two components: a virtual page number (VPN) and an offset. How many bits are in the VPN?

    3. Only eight 8-KB pages in a 64-KB address space.

    (c) How many bits are in the offset?

    16 (VA) - 3 (VPN) = 13.
    Alternately: an 8KB page of course requires 13 bits to address each byte (213 = 8192).

    (d) Now assume that the OS is using a linear page table, as discussed in class. How many entries does this linear page table contain?

    One entry per virtual page. Thus, 8.

    Now assume you again have a small virtual address space of size 64 KB, that the system again uses paging, but
    that each page is of size 4 bytes (note: not KB!).


    (a) How many bits are in a virtual address in this system?

    Still 16. The address space is the same size.

    (b) How many bits are in the VPN?

    14.

    (c) How many bits are in the offset?

    Just 2 (4 bytes).

    (d) Again assume that the OS is using a linear page table. How many entries does this linear page table
    contain?

    2**14, or 16,384.
    ____________________________________________________________________________________

     Consider the following segment table:
    Segment  Base  Length
        0   219    600
        1  2300     14
        2    90    100
        3  1327    580
        4  1952     96
    What are the physical addressed for the following logical addresses?
    (a) 0,430
    (b) 1,10
    (c) 2,500
    (d) 3,400
    (e) 4,112
    • (a) 219 + 430 = 649
    • (b) 2300 + 10 = 2310
    • (c) illegal reference; traps to operating system
    • (d) 1327 + 400 = 1727
    • (e) illegal reference; traps to operating system 

    ___________________________________________________________________________


    Consider a paging system with the page table stored in memory.
    (a) If a memory reference takes 200 nanoseconds, how long does a paged memory reference take?
    (b) If we add associative registers, and 75% of all page-table references are found in the associative registers, what is the effective memory reference time? (Assume that finding a page-table entry in the associative registers takes zero time, if the entry is there.)
    • 400 nanoseconds. 200 ns to access the page table plus 200 ns to access the word in memory.
    • 250 nanoseconds. 75% of the time it's 200 ns, and the other 25% of the time it's 400ns, so the equation is:
      e.a. = (.75*200)+(.25*400)
      ________________________________________________________________________

      A certain computer provides its users with a virtual memory space of 2**32 bytes. The computer has 2**18 bytes of physical memory. The virtual memory is implemented by paging, and the page size is 4K bytes. A user process generated the virtual address 11123456. Explain how the system establishes the corresponding physical location.

      * The virtual address in binary form is

      0001 0001 0001 0010 0011 0100 0101 0110

      Since the page size is 2**12, the page table size is 2**20. Therefore, the low-order 12 bits (0100 0101 0110) are used as the displacement into the page, while the remaining 20 bits (0001 0001 0001 0010 0011) are used as the displacement in the page table.

      __________________________________________________________________________________

    Round robin scheduling questions

    1. Consider N processes sharing the CPU in a round-robin fashion (N>=2). Assume that each context switch takes S msec and that each time quantum is Q msec. For simplicity, assume that processes never block on any event and simply switch between the CPU and the ready queue.

    In the following your answers should be functions of N, S and T.

    a) Find the maximum value of Q such that no process will ever go more than T msec

    Time taken for one process per quantum = quantum,Q+context switch,S

    Max wait time, T = N(Q+S)

    T = NQ+NS
    Q = (T-NS)/N

    b) Find the maximum value of Q such that no process will ever go more than T msecs between executing instructions on the CPU?

    Max wait time, T = N(Q+S) - Q ie.last instruction just before context switch executes at the end of the quantum of the first time when process executes..
    T = NQ+NS-Q
    T = Q(N-1)+NS
    Q = (T-NS)/(N-1)

    2. Suppose that there are two processes, PH and PL, running in a system. Each process is single-threaded. The operating system’s scheduler is preemptive and uses round-robin scheduling with a quantum of q time units.

    The scheduler supports two priority levels, HIGH and LOW. Processes at LOW priority will run only if there are no runnable HIGH priority processes. Process PH is a HIGH priority process.
    It behaves as described in the following pseudo-code:

    while (TRUE) do
    compute for tc time units
    block for tb time units to wait for a resource
    end while

    That is, if this process were the only one running in the system, it would alternate between running for tc units of time and blocking for tb units of time. Assume that tc is less than q.

    Process PL is a low priority process. This process runs forever, doing nothing but computation. That is, it never blocks waiting for a resource.

    a. For what percentage of the time will the low priority process PL be running in this system?Express your answer in terms of tb and tc.

    tb/(tb + tc)

    b. Repeat part (a), but this time under the assumption that there are two HIGH priority processes (PH1 and PH2) and one LOW priority process (PL). Assume that each HIGH priority process waits for a different resource. Again, express your answer in terms of tb and tc. Your answer should be correct for all tb greater than 0 and all 0 less than tc less than q.

    (tb−tc)/(tb+tc)       if tc is less than tb

    0                          if tc greater than or equal to tb
    ------------------------------------------------------------------------------------------------------------
    Suppose a processor uses a prioritized round robin scheduling policy. New processes are assigned an initial quantum of length q. Whenever a process uses its entire quantum without blocking, its new quantum is set to twice its current quantum. If a process blocks before its quantum expires, its new quantum is reset to q. For the purposes of this question, assume that
    every process requires a finite total amount of CPU time.
    (a) Suppose the scheduler gives higher priority to processes that have larger quanta. Is starvation possible in this system? Why or why not?
    No, starvation is not possible. Because we assume that a process will terminate, the worst
    that can happen is that a CPU bound process will continue to execute until it completes.
    When it finishes, one of the lower priority processes will execute. Because the I/O bound
    processes will sit on the low priority queue, they will eventually make it to the head of the
    queue and will not starve.
    (b) Suppose instead that the scheduler gives higher priority to processes that have smaller quanta. Is starvation possible in this system? Why or why not?
    Yes, starvation is possible. Suppose a CPU bound process runs on the processor, uses its
    entire quantum, and has its quantum doubled. Suppose a steady stream of I/O bound processes
    enter the system. Since they will always have a lower quantum and will be selected for
    execution before the process with the doubled quantum, they will starve the original process.
    _______________________________________________________________
    Assume that 3 processes all with requirements of 1 second of CPU time each and
    no I/O arrive at the same time.

    a)What will be the average response time (i.e., average time to
    completion) for the processes Round Robin (RR) scheduling assuming a timeslice of 0.1 sec and no overhead for context switches (i.e., context switches are free).


    Answer: 2.9 seconds

    Explanation:

    Time for completion for process A =0.28
    Time for completion for process B =0.29
    Time for completion for process C = 0.30

    Average time for completion =0. 29
    ________________________________________________________________________________________________________

    Suppose that the operating system is running a round-robin scheduler with a 50 msec time quantum. There are three processes with the following characteristics:

    * Process A runs for 60 msec, blocks for 100 msec, runs for 10 msec and terminates.
    * Process B runs for 70 msec, blocks for 40 msec, runs for 20 msec, and terminates.
    * Process C runs for 20 msec, blocks for 80 msec, runs for 60 msec, and terminates.

    Process A enters the system at time 0. Process B enters at time 10 msec. Process C enters at time 20 msec. Trace the evolution of the system. You should ignore the time required for a context switch. The time required for process P to block is the actual clock time between the time that P blocks and the time that it unblocks, regardless of anything else that is happening.
    Answer:

    Time Running process Events
    0-50 A B enters at time 10. C enters at time 20.
    50-100 B
    100-120 C C blocks until time 200.
    120-130 A A blocks until time 230.
    130-150 B B blocks until time 190
    150-190 Idle B unblocks at time 190
    190-210 B C unblocks at time 200. B terminates at time 210
    210-260 C A unblocks at time 230.
    260-270 A A terminates at time 270.
    270-280 C C terminates at time 280.



    _______________________________________________________________________________________________
    Consider a variant of the round-robin scheduling algorithm where the entries in the ready queue are pointers to process-control-blocks.

    1. What would be the effect of putting two pointers to the same process in the ready queue?

    Doubling the time given to that process.
    2. What would be the major advantages and disadvantages of this scheme?

    Simple scheme which would provide some priority work with minimal modification to scheduler. But, overhead for managing pointers is a nuisance -- what if the process is io waiting or done? Have to remove BOTH pointers from ready queue, etc. Also may increase overhead if same process runs back-to-back -- it was not necessary to switch contexts.
    3. How would you modify the basic round-robin algorithm to achieve the same effect without duplicate pointers?

    Add a simple quantum indicator to PCB.
    _______________________________________________________________________________________________

    For each of the following statements, indicate whether you think it is probably true (T) or probably false (F). Then give a brief (one sentence) reason. There is not necessarily a single correct answer to each question, so your one sentence explanation is the most important part of your answer.

    1. Small time slices always improve the average completion time of a system.

    Probably false: Small time slices will sometimes improve the average response of the system. If the slice is too small, the context switching time will start to dominate the useful computation time and everything (including response time) will suffer.

    2. Using a round robin scheduler, a large time slice is bad for interactive users.

    Probably true: Large time slices can allow non-interactive processes keep control of the CPU for longer periods of time, causing the interactive processes to be less responsive.

    3. Shortest Job First (SJF) or Shortest Completion Time First (SCTF) scheduling is difficult to build on a real operating system.

    Probably true: SCTF scheduling requires knowledge of how much time a process is going to take. This requires future knowledge. You might require a user to specify the maximum amount of time that a process could run (and kill it if it exceeds this amount), then use a variant on SCTF.

    ________________________________________________________________________________

    Wednesday, September 22, 2010

    5 Variable Karnaugh Map Solution

    Simplify the Boolean function
    F(A,B,C,D,E)  = Σ (0,2,4,6,9,11,13,15,17,21,25,27,29,31)

    Writing decimals in binary,

     Decimal    A    B    C    D    E
         0           0    0     0    0    0
         2           0    0     0    1    0
         4           0    0     1    0    0
         6           0    0     1    1    0
         9           0    1     0    0    1
         11         0    1     0    1    1  
         13         0    1     1    0    1
         15         0    1     1    1    1
         17         1    0     0    0    1
         21         1    0     1    0    1
         25         1    1     0    0    1
         27         1    1     0    1    1
         29         1    1     1    0    1
         31         1    1     1    1    1

    Construct two Karnaugh maps for variables A,B,C and D when  E=0 and E=1




    From Karnaugh map E=0,  F0 = A'B'E'

    From Karnaugh map E=1,  F1 = BE+ AD'E

    F  =   F0+  F1

    F   =    A'B'E'   +  BE  +   AD'E

    Wednesday, September 8, 2010

    Recurrence relations examples


    Solve the recurrence relation T(n) = T(n/2) + lg(n) where T(1) = 1 and n = 2k for a nonnegative integer k. Your answer should be a precise function of n in closed form. Note that lg represents the log function base 2.

    T(n) = T(n/2) + lg(n)

    T(n/2) = T(n/4) + lg(n/2)

    T(n/4) = T(n/8) + lg(n/4)

    T(n/8) = T(n/16) + lg(n/8)


    Substituting for T(n)

    T(n) = T(n/2) + lg(n)

    = T(n/4) + lg(n/2)+lg(n)

    = T(n/8)+ lg(n/4)+ lg(n/2)+lg(n)

    = T(n/16)+lg(n/8)+ lg(n/4)+ lg(n/2)+lg(n)


    ----------------------------------------------------------

    ----------------------------------------------------------

    Suppose n= 2**k

    T(n) = 1 + lg (n. n/2 . n/4. . . . . n/2**k-1)

    = 1+ lg(2**k  . 2**k-1 .   2**k-2 .  …… . 2)

    = 1+ lg( 2 **(1+2+3+ - - - +k))

    = 1 + (1+2+3+ ----+k)

    = 1+ k(k+1)/2

    ______________________________________________________________________________

    Solve the recurrence T(n) = T(n-1) + n

    T(n)    = T(n-1) + n
    T(n-1) = T(n-2) + n-1
    T(n-2) = T(n-3) + n-2
    T(n-3) = T(n-4) + n -3

     T(n)  =  T(n-1) + n
             =   T(n-2) + n-1+n
             =   T(n-3) + n-2+n-1+n
             =   T(n-4) + n-3+n-2+n-1+n
    -----------------------------------------------

            Consider n= 2**k
     T(n)  =  T(n-k) + n+n-1+n-2+n-3+ -------------+n-(k-1)
             =  T(n-k) +  n(n-1) - k(k-1)/2
             = T(n-k) +  n**2 - n -lgn(lgn-1)/2
           
    Therefore, asymptotic complexity is n**2



    Tuesday, August 31, 2010

    Delete a linked list using recursion in C++

    #include < iostream >
    using namespace std;

    struct Node{
        int num;
        Node* next;
    };

    //Here address of pointer to the list is passed so that head of the  list  will not be a local variable.

    void DeleteListRecursion(Node*& list){
        if(list == NULL)
            return;
        else
         DeleteListRecursion(list->next);
         delete(list);
         list = NULL;
    }



    Node* Insert(int number, Node* list){
        Node* node = new Node;
        node->num = number;
        node->next = list;
        return node;
    }

    //TEST

    int main(){
           
        Node* list = NULL;

        list = Insert(5,list);
        list = Insert(7,list);
        list = Insert(9,list);
        list = Insert(4,list);
        list = Insert(6,list);
        list = Insert(3,list);
       
        DeleteListRecursion(list);

        return 0;
    }

    Saturday, August 28, 2010

    Data Structures You Should Know

    • UnSorted List Using Arrays
    • UnSorted List Using Linked List
    • Sorted List Using Arrays
    • Sorted List Using Linked List
    • Doubly Linked List
    • Circular List
    • Stack Using Arrays
    • Stack Using LinkedList
    • Queue Using arrays
    • Queue Using LinkedList
    • Recursion Problems
    • Binary Tree
    • Sorting
      • Bubble Sort           Code          Example
      • Selection Sort        Code          Example
      • Insertion Sort         Code          Example
      • QuickSort              Code          Example
      • MergeSort             Code          Example
      • HeapSort             Code          Example
      • Radix Sort             Code          Example
      • Hashing

      Tuesday, June 15, 2010

      Chomsky Hierarchy Diagram for Languages.


      The diagram shows how different classes of languages such as regular, context free, context sensitive, P, NP, PSAPACE, NPSPACE, EXPTIME, NEXPTIME, EXPSPACE, ACCEPTABLE, DECIDABLE, CO-ACCEPTABLE etc are related to each other.

      Half-Sat Problem With Example

      Half-SAT = {F | F is a CNF formula with 2n variables and there is a satisfying assignment in which n variables are set to True and n variables are set to False}.
      Show that Half-SAT is NP-Hard.


      We can show that half-sat is NP-hard by reducing sat to half-sat. We can show that if half-sat has a solution sat also has a solution.

      Let T be a turing machine(transducer) which reduces sat to half-sat. T takes F as input.
      Let F has variables x1,x2,......xn.
      T(F) =  Construct a new CNF formula F' as follows.
                  F' will have variables x1,x2,.......xn from F and new variables y1,y2,...........yn such that xi = ‾yi
                  If a clause is of the form (x1 U x2), convert it into (x1 U x2) ^( ‾y1  U  ‾y2).
      Output(F')
          

      Example 1
      Let F = (x1 U x2 U ‾x3) and  x1=True,  x2=False, x3= True
      F = T U F U T = T
      Introduce three new variables y1,y2 and y3 such that
      x1 =  ‾y1
      x2 =  ‾y2
      ‾x3 =  y3


      F' = (x1 U x2 U ‾x3) ^ (  ‾y1 U ‾y2 U y3).
       x1  = T    y1  =F

      x2  = F    y2  =T
      x3  = T    y3  =F

      Here three variables are assigned True and other three variables are assigned False. Therefore the expression is in half-sat.
      Assigning values to F',  F' = ( T U F U T) ^ (T U F U T) =  True.

      Hence F' evaluates to  true iff F evaluates to  true.

      Let x1=False, x2 = False, x3=False
      F=  false U false U false = False
      F' = (F U F U F) ^ (F U F U F) = F
      Hence F' evaluates to  false iff F evaluates to  false.

      Friday, June 11, 2010

      NP- complete Problems with variations

      K-clique                           video
      Hamiltonian Path                   video lecture
      • Does a hamiltonian path exist in G.
      • Does a hamiltonian path exist from node s to t
      • k-link path 
      • Hamiltonian Circuit       video
      SAT Problems                    video
      Subset Sum Problem              video
      • Partition                       video
      • Multiset                        video
      3-COLOR

      Thursday, June 10, 2010

      Half Clique Problem with examples ( Complexity theory )

      Half-clique problem is described as follows. Given a graph G with n number of vertices, does there exist a clique of G consisting of exactly  half the nodes of G? Show that HALF-CLIQUE is NP-hard by reducing CLIQUE to  HALF-CLIQUE.

       Let f be a transducer which does the reduction.

      f(G,k) =  Construct G' as follows
                    Add n more vertices to G.
                    Select n-k of the newly added vertices, connect them to each other and to all  original vertices in G.
                   
      Output (G')

      Here adding n-k vertices to G can be done in polynomial time. So reduction is done in polynomial time.
      Yes Instance

      In the following example G has 5 nodes. Let k=3. This is a yes instance since G has a clique of k=3( nodes A,B and E).










      Construct G' by adding 5 more nodes (F,G,H,I,J)  to graph G. Connect 5-3=2 of them to each other and to original nodes of G.












      G' has five-clique (A,B,E,F and G). 
      G' will not have 5-clique unless G already has a 3 clique.

      No Instance

      Try yourself.:
      Remove any of the edges forming 3 clique and try to construct G'. Check whether G' can have a 5-clique.


      Clique can be reduced to any fractionof clique using the same logic. To solve (1/m)th clique, add (m-1)n vertices to graph G and connect n-k vertices.
      For example, to solve quarter-clique, add 3n vertices to G and fully connect n-k new vertices.

      Thursday, May 20, 2010

      Oracle Trouble shooting

       When I am trying to sign in to Oracle 11g  in windows xp , I am getting the error  'ORA-12560: TNS:protocol adapter error'

      Solution:
      Try1:
      set local=databasename
      For example, if name of database is orcl, command will be
      C:\ set local = ORCL

      Then log in to sqlplus 
      C:\ sqlplus / as sysdba
      ___________________________________________________________________________________
      Try 2

      If try1 does not work,

      In command prompt do the following:
      C:\ set ORACLE_SID =  databasename
       Important:  The database name has to be in uppercase letters. 

      For example, if name of database is orcl, command will be
      C:\ set ORACLE_SID = ORCL

      Then log in to sqlplus 
      C:\ sqlplus / as sysdba

      SQL*Plus: Release 11.1.0.6.0 - Production on Sun Jun 20 00:06:58 2010


      Copyright (c) 1982, 2007, Oracle.  All rights reserved.


      Connected to:
      Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production
      With the Partitioning, OLAP, Data Mining and Real Application Testing options

      Now you are connected to the database.
      ____________________________________________________________________________________

      Friday, April 16, 2010

      Turing Machine ( True or False )

      1. A Universal Turing Machine can compute anything that any other Turing Machine could possibly compute.
      True

      2.The Turing Test is a test of whether a problem can be solved by a Turing Machine.
      True

      3. Every acceptable language is also decidable.
      False

      4. Decidability is a special case of decidability
      True

      5. Regular languages are decidable
      True

      6. Context free languages are not decidable
      False

      Saturday, March 13, 2010

      Interesting Algorithms

      1. Let A be a list of n elements in non-decreasing order where some elements are replicated.
      The problem is to find the element that appear most frequently. Give an O(k log n) time
      algorithm to solve the problem where k denotes the number of distinct elements in A.


      2. You are given a list A = [a1; a2; - - - ; an] of n distinct numbers in an arbitrary order.
      You are supposed to find two numbers i and j from A such that (i) i < j, (ii) j > i, and
      (iii) satisfying (i) and (ii), aj - ai is minimum over all possible such pairs. Give an O(n) time
      algorithm.


      3. A carpenter has a piece of wood of a certain length that must be cut at positions a1, a2 ..., an where ai is the distance from the left end of the original piece of wood. Notice that after making the first cut, the carpenter now has two pieces of wood; after making the second cut, the carpenter has three pieces of wood, etc. Assume that the cost of making a cut in a piece of wood of length l is equal to l, and is the same no matter which position in that piece of wood is being cut. Let L be the length of the original piece of wood.
      Derive the recurrence relation which could be used to design a recursive algorithm to find the minimum total cost for making all the cuts.


      4. Describe a Θ(n lg n)-time algorithm, that given a set of n integers and another
      integer x, determines whether or not there exist two elements in S whose sum is exactly x. Write
      pseudocode.
      Hint: Sort using mergesort and iterate once after sorting. Θ(n lg n+n) = Θ(n lg n)


      5. Suppose you are given an array A containing n sorted elements followed by lgn unsorted elements. Thus, entire array contains N = n+lgn elements. Can the entire array sorted in O(n) time.

      6.  You are given an array of n numbers. Write an algorithm with O(n)=nlogn  that returns the number of distinct numbers in the array.   

      Friday, March 12, 2010

      Minimum Spanning Tree - True or False

      1. In an undirected graph, the shortest path between two nodes lies on some minimum spanning
      tree.
      A: False.

      2. If the edges in a graph have different weights, then the minimum spanning tree is unique.
      A: True.

      3. If the edge with maximum weight belongs to a cycle, then there exists some MST that
      does not contain this edge.
      A: True

      4. Adding a constant to every edge weight does not change the minimum spanning tree.
      A: True

      5. There can be more than one minimum spanning trees if the weight of the edges are all distinct
      A.False

      6. If all weights are the same, every spanning tree is minimum.
      A. True

      7. Greedy algorithm runs in exponential time
      A. False

      8. A minimum spanning tree should contain all edges of the graph
      A. False

      9. A minimum spanning tree should contain all vertices of the graph
      A.True

      10.Adding an edge to a spanning tree of a graph G always creates a cycle.
      A.False

      11. Adding an edge to a spanning tree connecting two existing vertices of a graph G always creates a cycle.
      A. True

      12. For any cycle in a graph, the cheapest edge in the cycle is in a minimum spanning tree.
      A. False