[algogeeks] Re: Blocked/Unrolled linked list with no duplicates and sorted
Anyone ?
On Jul 26, 10:27 pm, banu varun.nagp...@gmail.com wrote:
Hi,
Basically I am trying to create a blocked linked list(unrolled linked
list) with following properties
- Configurable number of elements in each node
- No duplicate elements in the unrolled linked list
- Linked list is sorted either during insertion or after creating the
linked list
- In place
Assuming I need to create a sorted unrolled linked list with no
duplicate elements with block size say 2
Example: 10,2,4,2,5,7,9.11,11,5
Final blocked linked list: (2,4)-(5,7)-(9,10)-(11,x) or in reverse
order
Note: x means unutilized location in the array wihtin the node. In
case there are not enough elements to insert in a node, some memory
allocated for a node is unutilized
// Following is node structure
#define ARRAY_SZ 2
typedef struct node
{
struct node* next;
long long int elements[ARRAY_SZ];
long long int elemIndex;
}NODE, *NODE_PTR;
Can you suggest me a way to do this correctly and efficiently? It
could be an pseudo text or C-code.
Thanks
Varun
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[algogeeks] Blocked/Unrolled linked list with no duplicates and sorted
Hi,
Basically I am trying to create a blocked linked list(unrolled linked
list) with following properties
- Configurable number of elements in each node
- No duplicate elements in the unrolled linked list
- Linked list is sorted either during insertion or after creating the
linked list
- In place
Assuming I need to create a sorted unrolled linked list with no
duplicate elements with block size say 2
Example: 10,2,4,2,5,7,9.11,11,5
Final blocked linked list: (2,4)-(5,7)-(9,10)-(11,x) or in reverse
order
Note: x means unutilized location in the array wihtin the node. In
case there are not enough elements to insert in a node, some memory
allocated for a node is unutilized
// Following is node structure
#define ARRAY_SZ 2
typedef struct node
{
struct node* next;
long long int elements[ARRAY_SZ];
long long int elemIndex;
}NODE, *NODE_PTR;
Can you suggest me a way to do this correctly and efficiently? It
could be an pseudo text or C-code.
Thanks
Varun
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[algogeeks] Re: a google question
Nice question:
1. |A| = |B| i.e I assume their cardinality is equal
2. A(n) = { a1, a2 a3, ...aN} such that a1=a2=a3...=aN
3. B(n) = { b1, b2 b3, ...bN} such that b1=b2=b3...=bN
4. S(n^2) = A x B = {(a1,b1), (a1,b2)(a1,bN),
(a2,b1), (a2,b2)(a2,bN),
(aN,b1), (aN,b2)(aN,bN)}
I assume each pair is stored as a sum i.e ai + bi and also that I
have paired them in a way such that we find a pair ai bi for some
i in 1..N and and a(i-1) = b(i-1)
A first observation is that in the worst case, the first 2N numbers in
S will contain the final result of N numbers.
i.e in (a1,b1), (a1,b2)(a1,bN), (a2,b1), (a2,b2)(a2,bN)
In the best case first N numbers in S will contain the final N numbers
(already sorted in decreasing order)
i.e in (a1,b1), (a1,b2)(a1,bN)
Now, if we consider again the worst case scenario, then we can first
divide 2N numbers in two groups of size N each and each of this group
is already sorted in decreasing order.
i.e (a1,b1), (a1,b2)(a1,bN) and (a2,b1), (a2,b2)(a2,bN)
Now we can simply apply Merge Algorithm on these 2 already sorted
arrays of size N each in O(N) time, which solves the problem
I can be wrong only if the the results lie outside first 2N numbers,
which I hope is not the case(then I think its not possible to solve in
O(n) but in O(nlogn)).
On Apr 30, 2:05 pm, divya sweetdivya@gmail.com wrote:
Given two sorted postive integer arrays A(n) and B(n) (W.L.O.G, let's
say they are decreasingly sorted), we define a set S = {(a,b) | a \in
A
and b \in B}. Obviously there are n^2 elements in S. The value of such
a pair is defined as Val(a,b) = a + b. Now we want to get the n pairs
from S with largest values. The tricky part is that we need an O(n)
algorithm.
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[algogeeks] Re: a google question
Nice question:
1. |A| = |B| i.e I assume their cardinality is equal
2. A(n) = { a1, a2 a3, ...aN} such that a1=a2=a3...=aN
3. B(n) = { b1, b2 b3, ...bN} such that b1=b2=b3...=bN
4. S(n^2) = A x B = {(a1,b1), (a1,b2)(a1,bN),
(a2,b1), (a2,b2)(a2,bN),
(aN,b1), (aN,b2)(aN,bN)}
assuming we have added in a way such that we find a pair ai bi,
for some i in 1..N such that a(i-1) = b(i-1)
A first observation is that in the worst case, the first 2N numbers in
S will contain the final result of N numbers.
i.e in (a1,b1), (a1,b2)(a1,bN), (a2,b1), (a2,b2)(a2,bN)
In the best case first N numbers in S will contain the final N numbers
(already sorted in decreasing order)
i.e in (a1,b1), (a1,b2)(a1,bN)
Now, if we consider again the worst case scenario, then we can first
divide 2N numbers in two groups of size N each and each of this group
is already sorted in decreasing order.
i.e (a1,b1), (a1,b2)(a1,bN) and (a2,b1), (a2,b2)(a2,bN)
Now we can simply apply Merge Algorithm on these 2 already sorted
arrays of size N each in O(N) time, which solves the problem
I can be wrong only if the the results lie outside first 2N
numbers(which I hope is not the case).
On Apr 30, 2:05 pm, divya sweetdivya@gmail.com wrote:
Given two sorted postive integer arrays A(n) and B(n) (W.L.O.G, let's
say they are decreasingly sorted), we define a set S = {(a,b) | a \in
A
and b \in B}. Obviously there are n^2 elements in S. The value of such
a pair is defined as Val(a,b) = a + b. Now we want to get the n pairs
from S with largest values. The tricky part is that we need an O(n)
algorithm.
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[algogeeks] Alternative Dta Structures for Cache Inefficient Linked Lists
Hi, I had been thinking about this problem from quite sometime. Linked lists are good dynamic data structures and solve the main problems associated with arrays(static memory allocation) On the other hand, one of the biggest disadvantages of linked lists is that their cache utilization is extremely poor. This results mainly from poor spatial locality because nodes of linked list are allocated in non-sequential memory locations. So when one accesses a node of linked list, a single cache line(fixed bunch of bytes) is fetched, and as the other nodes are present far in memory, the cache line most of the time will not contain other nodes. So every time a new node is accessed, the previous cache line has to be flushed and replaced by new cache line containing new node. This means on every access of node we pay the cost of reading data from main memory(which is very expensive) and bringing it into cache Main problem is that the poor cache utilization can sometimes result very bad extremely performance especially if the program is memory intensive (uses lot of heap memory) My question is that are their any other data structures which provide the benefits of linked lists (using dynamic memory allocation) but are as efficient as arrays in context of cache utilization? Thanks Varun -- You received this message because you are subscribed to the Google Groups Algorithm Geeks group. To post to this group, send email to algoge...@googlegroups.com. To unsubscribe from this group, send email to algogeeks+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/algogeeks?hl=en.
