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May 25, 2008

Processor Overview

The Opteron is AMD's x86 server processor line, and was the first processor to implement the AMD64 instruction set architecture (known generically as x86-64). It was released on April 22, 2003 with the SledgeHammer core (K8) and was intended to compete in the server market, particularly in the same segment as the Intel Xeon processor. Processors based on the AMD K10 microarchitecture (codenamed Barcelona) were announced on September 10, 2007 featuring a new quad-core configuration.

 

  • AMD Opteron
  • AMD Opteron 64
  • AMD Athlon 64 FX
  • AMD Turion
  • AMD Sempron




 

 

Keywords: AMD processor

Posted by Computer Architecture - nick | 0 comment(s)


May 23, 2008

Today, i am going to tell you about the AMD 64 Architecture overview. We are going to divide our session in few Blog Entries over a couple of days. I will cover the following topics :

+ Processor Overview

I. AMD64 Architecture Overview

   + Operating Modes

   + Register Set

   + Segmentation

   + Task Management

   + Interrupts and Exceptions

   + Demand Mode Paging

   + Instruction Set Extensions

   + x86 Virtualization Overview 

 II. CPU Microarchitecture

   + Processor Core Introduction and Terminology

   + Integer Pipeline

   + FPU Pipeline

   + Load/Store Unit

   + Caches

III. System Architecture

   + System Chip Components

   + Hypertransport

   + Configuration Space

   + PC Memory Technologies

   + System Power Up Process

   + APIC

   + Debug Registers

   + Performance Monitoring Registers

   + Machine Check Architecture

   + Power Management

 

 Keep looking this blog for further explanations and details of CPU.

 

 

Keywords: architecture, CPU, Debug, Memory, power management, Segmentation, Virtualization

Posted by Computer Architecture - nick | 0 comment(s)


May 17, 2008

Embedded software often runs on processors with limited computation power, thus optimizing the code becomes a necessity. In this article we will explore the following optimization techniques for C and C++ code developed for Real-time and Embedded Systems.
  1. Adjust structure sizes to power of two
  2. Place case labels in narrow range
  3. Place frequent case labels first
  4. Break big switch statements into nested switches
  5. Minimize local variables
  6. Declare local variables in the inner most scope
  7. Reduce the number of parameters
  8. Use references for parameter passing and return value for types bigger than 4 bytes
  9. Don’t define a return value if not used
  10. Consider locality of reference for code and data
  11. Prefer int over char and short
  12. Define lightweight constructors
  13. Prefer initialization over assignment
  14. Use constructor initialization lists
  15. Do not declare “just in case” virtual functions
  16. In-line 1 to 3 line functions

Adjust structure sizes to power of two

When arrays of structures are involved, the compiler performs a multiply by the structure size to perform the array indexing. If the structure size is a power of 2, an expensive multiply operation will be replaced by an inexpensive shift operation. Thus keeping structure sizes aligned to a power of 2 will improve performance in array indexing.

Place case labels in narrow range

If the case labels are in a narrow range, the compiler does not generate a if-else-if cascade for the switch statement. Instead, it generates a jump table of case labels along with manipulating the value of the switch to index the table. This code generated is faster than if-else-if cascade code that is generated in cases where the case labels are far apart. Also, performance of a jump table based switch statement is independent of the number of case entries in switch statement.

Place frequent case labels first

If the case labels are placed far apart, the compiler will generate if-else-if cascaded code with comparing for each case label and jumping to the action for leg on hitting a label match. By placing the frequent case labels first, you can reduce the number of comparisons that will be performed for frequently occurring scenarios. Typically this means that cases corresponding to the success of an operation should be placed before cases of failure handling.

Break big switch statements into nested switches

The previous technique does not work for some compilers as they do not generate the cascade of if-else-if in the order specified in the switch statement. In such cases nested switch statements can be used to get the same effect.
To reduce the number of comparisons being performed, judiciously break big switch statements into nested switches. Put frequently occurring case labels into one switch and keep the rest of case labels into another switch which is the default leg of the first switch.
Splitting a Switch Statement

//This switch statement performs a switch on frequent 
//messages and handles the infrequent messages
//with another switch statement in the default
//leg of the outer
// switch statement
pMsg = ReceiveMessage();
switch (pMsg->type)
{
case FREQUENT_MSG1:
handleFrequentMsg1();
break;
case FREQUENT_MSG2:
handleFrequentMsg2();
break;
. . .
case FREQUENT_MSGn:
handleFrequentMsgn();
break;
default:
// Nested switch statement for
//handling infrequent messages.
switch (pMsg->type)
{
case INFREQUENT_MSG1:
handleInfrequentMsg1();
break;
case INFREQUENT_MSG2:
handleInfrequentMsg2();
break;
. . .
case INFREQUENT_MSGm:
handleInfrequentMsgm();
break;
}
}

Minimize local variables

If the number of local variables in a function is less, the compiler will be able to fit them into registers. Hence, it will be avoiding frame pointer operations on local variables that are kept on stack. This can result in considerable improvement due to two reasons:

  All local variables are in registers so this improves performance over accessing them from memory.
? If no local variables need to be saved on the stack, the compiler will not incur the overhead of setting up and restoring the frame pointer.

Declare local variables in the inner most scope

Do not declare all the local variables in the outermost function scope. You will get better performance if local variables are declared in the inner most scope. Consider the example below; here object a is needed only in the error case, so it should be invoked only inside the error check. If this parameter was declared in the outermost scope, all function calls would have incurred the overhead of object a’s creation (i.e. invoking the default constructor for a).
Local varialble scope

int foo(char *pName)
{
if (pName == NULL)
{
A a;
...
return ERROR;
}
...
return SUCCESS;
}

Reduce the number of parameters

Function calls with large number of parameters may be expensive due to large number of parameter pushes on stack on each call. For the same reason, avoid passing complete structures as parameters. Use pointers and references in such cases.

Use references for parameter passing and return value for types bigger than 4 bytes

Passing parameters by value results in the complete parameter being copied on to the stack. This is fine for regular types like integer, pointer etc. These types are generally restricted to four bytes. When passing bigger types, the cost of copying the object on the stack can be prohibitive. In case of classes there will be an additional overhead of invoking the constructor for the temporary copy that is created on the stack. When the function exits the destructor will also be invoked.

Thus it is efficient to pass references as parameters. This way you save on the overhead of a temporary object creation, copying and destruction. This optimization can be performed easily without a major impact to the code by replacing pass by value parameters by const references. (It is important to pass const references so that a bug in the called function does not change the actual value of the parameter.

Passing bigger objects as return values also has the same performance issues. A temporary return object is created in this case too.

Don’t define a return value if not used

The called function does not “know” if the return value is being used. So, it will always pass the return value. This return value passing may be avoided by not defining a return value which is not being used.

Consider locality of reference for code and data

The processor keeps data or code that is referenced in cache so that on its next reference if gets it from cache. These cache references are faster. Hence it is recommended that code and data that are being used together should actually be placed together physically. This is actually enforced into the language in C++. In C++, all the object’s data is in one place and so is code. When coding is C, the declaration order of related code and functions can be arranged so that closely coupled code and data are declared together.

Prefer int over char and short

With C and C++ prefer use of int over char and short. The main reason behind this is that C and C++ perform arithmetic operations and parameter passing at integer level, If you have an integer value that can fit in a byte, you should still consider using an int to hold the number. If you use a char, the compiler will first convert the values into integer, perform the operations and then convert back the result to char.

 

Lets consider the following code which presents two functions that perform the same operation with char and int.
Compaing char and int operations

char sum_char(char a, char b)
{
char c;
c = a + b;
return c;
}
 
int sum_int(int a, int b)
{
int c;
c = a + b;
return c;
}

A call to sum_char involves the following operations:

  1. Convert the second parameter into an int by sign extension (C and C++ push parameters in reverse)
  2. Push the sign extended parameter on the stack as b.
  3. Convert the first parameter into an int by sign extension.
  4. Push the sign extended parameter on to the stack as a.
  5. The called function adds a and b
  6. The result is cast to a char.
  7. The result is stored in char c.
  8. c is again sign extended
  9. Sign extended c is copied into the return value register and function returns to caller.
  10. The caller now converts again from int to char.
  11. The result is stored.

A call to sum_int involves the following operations:

  1. Push int b on stack
  2. Push int a on stack
  3. Called function adds a and b
  4. Result is stored in int c
  5. c is copied into the return value register and function returns to caller.
  6. The called function stores the returned value.

Thus we can conclude that int should be used for all interger variables unless storage requirements force us to use a char or short. When char and short have to be used, consider the impact of byte alignment and ordering to see if you would really save space. (Many processors align structure elements at 16 byte boundaries)?

Define lightweight constructors

As far as possible, keep the constructor light weight. The constructor will be invoked for every object creation. Keep in mind that many times the compiler might be creating temporary object over and above the explicit object creations in your program. Thus optimizing the constructor might give you a big boost in performance. If you have an array of objects, the default constructor for the object should be optimized first as the constructor gets invoked for every object in the array.

Prefer initialization over assignment

Consider the following example of a complex number::

Initialization and assignment

void foo()
{
Complex c;
c = (Complex)5;
}
 
void foo_optimized()
{
Complex c = 5;
}

In the function foo, the complex number c is being initialized first by the instantiation and then by the assignment. In foo_optimized, c is being initialized directly to the final value, thus saving a call to the default constructor of Complex.

Use constructor initialization lists

Use constructor initialization lists to initialize the embedded variables to the final initialization values. Assignments within the constructor body will result in lower performance as the default constructor for the embedded objects would have been invoked anyway. Using constructor initialization lists will directly result in invoking the right constructor, thus saving the overhead of default constructor invocation.? br /> In the example given below, the optimized version of the Employee constructor saves the default constructor calls for m_name and m_designation strings.
Constructor initialization lists

Employee::Employee(String name, String designation)
{
m_name = name;
m_designation = designation;
}
/* === Optimized Version === */
Employee::Employee(String name, String designation): m_name(name), m_destignation (designation)
{
}

Do not declare “just in case” virtual functions

Virtual function calls are more expensive than regular function calls so do not make functions virtual “just in case” somebody needs to override the default behavior. If the need arises, the developer can just as well edit the additional base class header file to change the declaration to virtual.

In-line 1 to 3 line functions

Converting small functions (1 to 3 lines) into in-line will give you big improvements in throughput. In-lining will remove the overhead of a function call and associated parameter passing. But using this technique for bigger functions can have negative impact on performance due to the associated code bloat. Also keep in mind that making a method inline should not increase the dependencies by requiring a explicit header file inclusion when you could have managed by just using a forward reference in the non-inline version.

 

Keywords: c, C++, constructor, embedded, optimization, pointer, real time, variable, virtual functions

Posted by nick | 0 comment(s)


May 08, 2008

Q: Given an array of size N in which every number is between 1 and N, 
determine if there are any duplicates in it.
Ans: I'll try to do it in O(N) w/o using any additional memory. The key is
to use content of the array as index into array, checking in O(1) if 
that number has been seen already.
bool HasDups(int * a, int N)
{
bool fHasDup = false;
for (int i = 0; i < N; i++) {
int index = a[i] % N;
if (a[index] > N) {
fHasDup = true;
break;
}
a[index] += N;
}

//restore the array
for (int j = 0; j < i; j++)
if (a[j] > N) a[j] %= N;

return fHasDup;
}

Keywords: duplicate, duplicate in array

Posted by Algorithm Design and Analysis - Anshul Malik | 0 comment(s)


void quicksort (int[] a, int lo, int hi)
{
// lo is the lower index, hi is the upper index
// of the region of array a that is to be sorted
int i=lo, j=hi, h;
int x=a[(lo+hi)/2];

// partition
do
{
while (a[i]<x) i++;
while (a[j]>x) j--;
if (i<=j)
{
h=a[i]; a[i]=a[j]; a[j]=h;
i++; j--;
}
} while (i<=j);

// recursion
if (lo<j) quicksort(a, lo, j);
if (i<hi) quicksort(a, i, hi);
}

Keywords: quick sort, sorting

Posted by Algorithm Design and Analysis - Anshul Malik | 0 comment(s)


January 13, 2008

hey guys i got this idea while studying the shortest path algos like djikstra nd warshall.

this can be done as a minor project... very simple thing to do.. we can write a symbian os program to find shortest path between 2 destinations on a map...... we will first have to make a map according to a scale, and then when the user enters the source and destination.. it will find out the shortest path between them using djikstra or warshall.......

we can also extend this algo to be of better use by also inculcating the traffic density, stoppages etc in the weigthage we give to each edge of the graph and then calculating the shortest path.....

 

i hope this is fine for minor projects......what do you think guys??...... 

Keywords: shortest path

Posted by Algorithm Design and Analysis - Anshul Malik | 0 comment(s)


January 07, 2008

well its really quite simple but will require loads of coding thing to be done. kind of a starter concept of AI where the computer decides the move.....

 Well the informal algo goes as follows... computer will calculate probability of winning and loosing for each possible  move  at each step in the game... if will then have to take a weighted average of those probability and calculate total winning probability... the move which gives him the highest total winning probability will be his move....... sounds simple isnt it but the coding of the same will ummmmm not complicated but will definately be lengthy.........

Keywords: algorithm to make tic tac toe, play tic tac toe with computer, tic tac toe

Posted by Algorithm Design and Analysis - sam | 0 comment(s)


you are given an expression like (a+((b+c)))..... here extra braces are provided on b+c... i mean like (b+c) is ok... but ((b+c)) isnt as it contains redundant brackets.. So for a given expression you have to tell whether expression contains redundant paranthesis or not.....?

 

I would like you people to try this question.... its quite simple .... i will provide you with the answer in next couple of days................... 

Posted by Algorithm Design and Analysis - sam | 2 comment(s)


hey people i would like to suggest an alternate approach to be used for radix sort.

The general approach is to apply counting sort on each digit of every number starting from the units place( now onwards LSB) and going upto the highest place(now onwards MSB)

eg suppose we have the numbers-> 219,357,557,639,426,620,345

so first it applies counting sort on LSB

hence the list will now be

620

345

426

357

557

219

639

then counting sort is applied to the tens plance and so on till MSB

Hence in this case we will have to check for each digits place uptil MSB.

Rather than doing this what we can do is start applying the counting sort from MSB, we will have following cases possible for each place(i.e. thousand, hundred, tens, units etc)

case 1: if all the digits (i.e of different numbers at that place) are different the counting sort will be applied and we will get the sorted list

eg if the numbers are : 128,532,457

then upon applying the modified radix sort we will first apply counting sort on the MSB's, since they are all different we will get the sorted list in one operation only

i.e. we will get 128,457,532

case 2: if 2 or more digits of the same place are equal, in this case we will apply the counting sort(preserving the ordering) and then sort for the next lower place

eg if the numbers are 253,146,223

then upon first applying counting  sort we get 146,253,223

then we check for next place and get the result as 146,223,253 

so we keep on applying these two cases until we get the sorted list. 

Therefore we can easily see that in case of the usual Radix sort, we will have to apply counting sort for each digit place while in case of this modification we can get the sorted list if at some place we get all the digits different ( we can easily use a counter for this)

I would like you people to think about this and tell me in which sorting the complexity will be less always... As far as i think it will be less in the second case.

Thank you 

Keywords: Radix Sort

Posted by Algorithm Design and Analysis - sam | 0 comment(s)


January 05, 2008

Keywords: education, elearning, future

Posted by nick | 0 comment(s)


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