To answer this question, I read this source code on github and found a problem with the second function.
The challenge is to write C code with various restrictions in terms of operators and language constructions to perform given tasks.
/*
* fitsShort - return 1 if x can be represented as a
* 16-bit, two's complement integer.
* Examples: fitsShort(33000) = 0, fitsShort(-32768) = 1
* Legal ops: ! ~ & ^ | + << >>
* Max ops: 8
* Rating: 1
*/
int fitsShort(int x) {
/*
* after left shift 16 and right shift 16, the left 16 of x is 00000..00 or 111...1111
* so after shift, if x remains the same, then it means that x can be represent as 16-bit
*/
return !(((x << 16) >> 16) ^ x);
}
Left shifting a negative value or a number whose shifted value is beyond the range of int has undefined behavior, right shifting a negative value is implementation defined, so the above solution is incorrect (although it is probably the expected solution).
Is there a solution to this problem that only assumes 32-bit two's complement representation?
The following only assumes 2's complement with at least 16 bits:
int mask = ~0x7FFF;
return !(x&mask)|!(~x&mask);
That uses a 15-bit constant; if that is too big, you can construct it from three smaller constants, but that will push it over the 8-operator limit.
An equivalent way of writing that is:
int m = 0x7FFF;
return !(x&~m)|!~(x|m);
But it's still 7 operations, so int m = (0x7F<<8)|0xFF; would still push it to 9. (I only added it because I don't think I've ever before found a use for !~.)
Related
I have an 18 bit integer that is in two's complement and I'd like to convert it to a signed number so I can better use it. On the platform I'm using, ints are 4 bytes (i.e. 32 bits). Based on this post:
Convert Raw 14 bit Two's Complement to Signed 16 bit Integer
I tried the following to convert the number:
using SomeType = uint64_t;
SomeType largeNum = 0x32020e6ed2006400;
int twosCompNum = (largeNum & 0x3FFFF);
int regularNum = (int) ((twosCompNum << 14) / 8192);
I shifted the number left 14 places to get the sign bit as the most significant bit and then divided by 8192 (in binary, it's 1 followed by 13 zeroes) to restore the magnitude (as mentioned in the post above). However, this doesn't seem to work for me. As an example, inputting 249344 gives me -25600, which prima facie doesn't seem correct. What am I doing wrong?
The almost-portable way (with assumption that negative integers are natively 2s-complement) is to simply inspect bit 17, and use that to conditionally mask in the sign bits:
constexpr SomeType sign_bits = ~SomeType{} << 18;
int regularNum = twosCompNum & 1<<17 ? twosCompNum | sign_bits : twosCompNum;
Note that this doesn't depend on the size of your int type.
The constant 8192 is wrong, it should be 16384 = (1<<14).
int regularNum = (twosCompNum << 14) / (1<<14);
With this, the answer is correct, -12800.
It is correct, because the input (unsigned) number is 249344 (0x3CE00). It has its highest bit set, so it is a negative number. We can calculate its signed value by subtracting "max unsigned value+1" from it: 0x3CE00-0x40000=-12800.
Note, that if you are on a platform, for which right signed shift does the right thing (like on x86), then you can avoid division:
int regularNum = (twosCompNum << 14) >> 14;
This version can be slightly faster (but has implementation-defined behavior), if the compiler doesn't notice that division can be exactly replaced by a shift (clang 7 notices, but gcc 8 doesn't).
Two problems: first your test input is not an 18-bit two's complement number. With n bits, two's compliment permits -(2 ^ (n - 1)) <= value < 2 ^ (n - 1). In the case of 18 bits, that's -131072 <= value < 131071. You say you input 249344 which is outside of this range and would actually be interpreted as -12800.
The second problem is that your powers of two are off. In the answer you cite, the solution offered is of the form
mBitOutput = (mBitCast)(nBitInput << (m - n)) / (1 << (m - n));
For your particular problem, you desire
int output = (nBitInput << (32 - 18)) / (1 << (32 - 18));
// or equivalent
int output = (nBitInput << 14) / 16384;
Try this out.
I saw the following line of code here in C.
int mask = ~0;
I have printed the value of mask in C and C++. It always prints -1.
So I do have some questions:
Why assigning value ~0 to the mask variable?
What is the purpose of ~0?
Can we use -1 instead of ~0?
It's a portable way to set all the binary bits in an integer to 1 bits without having to know how many bits are in the integer on the current architecture.
C and C++ allow 3 different signed integer formats: sign-magnitude, one's complement and two's complement
~0 will produce all-one bits regardless of the sign format the system uses. So it's more portable than -1
You can add the U suffix (i.e. -1U) to generate an all-one bit pattern portably1. However ~0 indicates the intention clearer: invert all the bits in the value 0 whereas -1 will show that a value of minus one is needed, not its binary representation
1 because unsigned operations are always reduced modulo the number that is one greater than the largest value that can be represented by the resulting type
That on a 2's complement platform (that is assumed) gives you -1, but writing -1 directly is forbidden by the rules (only integers 0..255, unary !, ~ and binary &, ^, |, +, << and >> are allowed).
You are studying a coding challenge with a number of restrictions on operators and language constructions to perform given tasks.
The first problem is return the value -1 without the use of the - operator.
On machines that represent negative numbers with two's complement, the value -1 is represented with all bits set to 1, so ~0 evaluates to -1:
/*
* minusOne - return a value of -1
* Legal ops: ! ~ & ^ | + << >>
* Max ops: 2
* Rating: 1
*/
int minusOne(void) {
// ~0 = 111...111 = -1
return ~0;
}
Other problems in the file are not always implemented correctly. The second problem, returning a boolean value representing the fact the an int value would fit in a 16 bit signed short has a flaw:
/*
* fitsShort - return 1 if x can be represented as a
* 16-bit, two's complement integer.
* Examples: fitsShort(33000) = 0, fitsShort(-32768) = 1
* Legal ops: ! ~ & ^ | + << >>
* Max ops: 8
* Rating: 1
*/
int fitsShort(int x) {
/*
* after left shift 16 and right shift 16, the left 16 of x is 00000..00 or 111...1111
* so after shift, if x remains the same, then it means that x can be represent as 16-bit
*/
return !(((x << 16) >> 16) ^ x);
}
Left shifting a negative value or a number whose shifted value is beyond the range of int has undefined behavior, right shifting a negative value is implementation defined, so the above solution is incorrect (although it is probably the expected solution).
Loooong ago this was how you saved memory on extremely limited equipment such as the 1K ZX 80 or ZX 81 computer. In BASIC, you would
Let X = NOT PI
rather than
LET X = 0
Since numbers were stored as 4 byte floating points, the latter takes 2 bytes more than the first NOT PI alternative, where each of NOT and PI takes up a single byte.
There are multiple ways of encoding numbers across all computer architectures. When using 2's complement this will always be true:~0 == -1. On the other hand, some computers use 1's complement for encoding negative numbers for which the above example is untrue, because ~0 == -0. Yup, 1s complement has negative zero, and that is why it is not very intuitive.
So to your questions
the ~0 is assigned to mask so all the bits in mask are equal 1 -> making mask & sth == sth
the ~0 is used to make all bits equal to 1 regardless of the platform used
you can use -1 instead of ~0 if you are sure that your computer platform uses 2's complement number encoding
My personal thought - make your code as much platform-independent as you can. The cost is relatively small and the code becomes fail proof
/*
* isLessOrEqual - if x <= y then return 1, else return 0
* Example: isLessOrEqual(4,5) = 1.
* Legal ops: ! ~ & ^ | + << >>
* Max ops: 24
* Rating: 3
*/
int isLessOrEqual(int x, int y)
{
int msbX = x>>31;
int msbY = y>>31;
int sum_xy = (y+(~x+1));
int twoPosAndNegative = (!msbX & !msbY) & sum_xy; //isLessOrEqual is FALSE.
// if = true, twoPosAndNegative = 1; Overflow true
// twoPos = Negative means y < x which means that this
int twoNegAndPositive = (msbX & msbY) & !sum_xy;//isLessOrEqual is FALSE
//We started with two negative numbers, and subtracted X, resulting in positive. Therefore, x is bigger.
int isEqual = (!x^!y); //isLessOrEqual is TRUE
return (twoPosAndNegative | twoNegAndPositive | isEqual);
}
Currently, I am trying to work through how to carry bits in this operator.
The purpose of this function is to identify whether or not int y >= int x.
This is part of a class assignment, so there are restrictions on casting and which operators I can use.
I'm trying to account for a carried bit by applying a mask of the complement of the MSB, to try and remove the most significant bit from the equation, so that they may overflow without causing an issue.
I am under the impression that, ignoring cases of overflow, the returned operator would work.
EDIT: Here is my adjusted code, still not working. But, I think this is progress? I feel like I'm chasing my own tail.
int isLessOrEqual(int x, int y)
{
int msbX = x >> 31;
int msbY = y >> 31;
int sign_xy_sum = (y + (~x + 1)) >> 31;
return ((!msbY & msbX) | (!sign_xy_sum & (!msbY | msbX)));
}
I figured it out with the assistance of one of my peers, alongside the commentators here on StackOverflow.
The solution is as seen above.
The asker has self-answered their question (a class assignment), so providing alternative solutions seems appropriate at this time. The question clearly assumes that integers are represented as two's complement numbers.
One approach is to consider how CPUs compute predicates for conditional branching by means of a compare instruction. "signed less than" as expressed in processor condition codes is SF ≠ OF. SF is the sign flag, a copy of the sign-bit, or most significant bit (MSB) of the result. OF is the overflow flag which indicates overflow in signed integer operations. This is computed as the XOR of the carry-in and the carry-out of the sign-bit or MSB. With two's complement arithmetic, a - b = a + ~b + 1, and therefore a < b = a + ~b < 0. It remains to separate computation on the sign bit (MSB) sufficiently from the lower order bits. This leads to the following code:
int isLessOrEqual (int a, int b)
{
int nb = ~b;
int ma = a & ((1U << (sizeof(a) * CHAR_BIT - 1)) - 1);
int mb = nb & ((1U << (sizeof(b) * CHAR_BIT - 1)) - 1);
// for the following, only the MSB is of interest, other bits are don't care
int cyin = ma + mb;
int ovfl = (a ^ cyin) & (a ^ b);
int sign = (a ^ nb ^ cyin);
int lteq = sign ^ ovfl;
// desired predicate is now in the MSB (sign bit) of lteq, extract it
return (int)((unsigned int)lteq >> (sizeof(lteq) * CHAR_BIT - 1));
}
The casting to unsigned int prior to the final right shift is necessary because right-shifting of signed integers with negative value is implementation-defined, per the ISO-C++ standard, section 5.8. Asker has pointed out that casts are not allowed. When right shifting signed integers, C++ compilers will generate either a logical right shift instruction, or an arithmetic right shift instruction. As we are only interested in extracting the MSB, we can isolate ourselves from the choice by shifting then masking out all other bits besides the LSB, at the cost of one additional operation:
return (lteq >> (sizeof(lteq) * CHAR_BIT - 1)) & 1;
The above solution requires a total of eleven or twelve basic operations. A significantly more efficient solution is based on the 1972 MIT HAKMEM memo, which contains the following observation:
ITEM 23 (Schroeppel): (A AND B) + (A OR B) = A + B = (A XOR B) + 2 (A AND B).
This is straightforward, as A AND B represent the carry bits, and A XOR B represent the sum bits. In a newsgroup posting to comp.arch.arithmetic on February 11, 2000, Peter L. Montgomery provided the following extension:
If XOR is available, then this can be used to average
two unsigned variables A and B when the sum might overflow:
(A+B)/2 = (A AND B) + (A XOR B)/2
In the context of this question, this allows us to compute (a + ~b) / 2 without overflow, then inspect the sign bit to see if the result is less than zero. While Montgomery only referred to unsigned integers, the extension to signed integers is straightforward by use of an arithmetic right shift, keeping in mind that right shifting is an integer division which rounds towards negative infinity, rather than towards zero as regular integer division.
int isLessOrEqual (int a, int b)
{
int nb = ~b;
// compute avg(a,~b) without overflow, rounding towards -INF; lteq(a,b) = SF
int lteq = (a & nb) + arithmetic_right_shift (a ^ nb, 1);
return (int)((unsigned int)lteq >> (sizeof(lteq) * CHAR_BIT - 1));
}
Unfortunately, C++ itself provides no portable way to code an arithmetic right shift, but we can emulate it fairly efficiently using this answer:
int arithmetic_right_shift (int a, int s)
{
unsigned int mask_msb = 1U << (sizeof(mask_msb) * CHAR_BIT - 1);
unsigned int ua = a;
ua = ua >> s;
mask_msb = mask_msb >> s;
return (int)((ua ^ mask_msb) - mask_msb);
}
When inlined, this adds just a couple of instructions to the code when the shift count is a compile-time constant. If the compiler documentation indicates that the implementation-defined handling of signed integers of negative value is accomplished via arithmetic right shift instruction, it is safe to simplify to this six-operation solution:
int isLessOrEqual (int a, int b)
{
int nb = ~b;
// compute avg(a,~b) without overflow, rounding towards -INF; lteq(a,b) = SF
int lteq = (a & nb) + ((a ^ nb) >> 1);
return (int)((unsigned int)lteq >> (sizeof(lteq) * CHAR_BIT - 1));
}
The previously made comments regarding use of a cast when converting the sign bit into a predicate apply here as well.
I am trying to convert a binary array to decimal in following way:
uint8_t array[8] = {1,1,1,1,0,1,1,1} ;
int decimal = 0 ;
for(int i = 0 ; i < 8 ; i++)
decimal = (decimal << 1) + array[i] ;
Actually I have to convert 64 bit binary array to decimal and I have to do it for million times.
Can anybody help me, is there any faster way to do the above ? Or is the above one is nice ?
Your method is adequate, to call it nice I would just not mix bitwise operations and "mathematical" way of converting to decimal, i.e. use either
decimal = decimal << 1 | array[i];
or
decimal = decimal * 2 + array[i];
It is important, before attempting any optimisation, to profile the code. Time it, look at the code being generated, and optimise only when you understand what is going on.
And as already pointed out, the best optimisation is to not do something, but to make a higher level change that removes the need.
However...
Most changes you might want to trivially make here, are likely to be things the compiler has already done (a shift is the same as a multiply to the compiler). Some may actually prevent the compiler from making an optimisation (changing an add to an or will restrict the compiler - there are more ways to add numbers, and only you know that in this case the result will be the same).
Pointer arithmetic may be better, but the compiler is not stupid - it ought to already be producing decent code for dereferencing the array, so you need to check that you have not in fact made matters worse by introducing an additional variable.
In this case the loop count is well defined and limited, so unrolling probably makes sense.
Further more it depends on how dependent you want the result to be on your target architecture. If you want portability, it is hard(er) to optimise.
For example, the following produces better code here:
unsigned int x0 = *(unsigned int *)array;
unsigned int x1 = *(unsigned int *)(array+4);
int decimal = ((x0 * 0x8040201) >> 20) + ((x1 * 0x8040201) >> 24);
I could probably also roll a 64-bit version that did 8 bits at a time instead of 4.
But it is very definitely not portable code. I might use that locally if I knew what I was running on and I just wanted to crunch numbers quickly. But I probably wouldn't put it in production code. Certainly not without documenting what it did, and without the accompanying unit test that checks that it actually works.
The binary 'compression' can be generalized as a problem of weighted sum -- and for that there are some interesting techniques.
X mod (255) means essentially summing of all independent 8-bit numbers.
X mod 254 means summing each digit with a doubling weight, since 1 mod 254 = 1, 256 mod 254 = 2, 256*256 mod 254 = 2*2 = 4, etc.
If the encoding was big endian, then *(unsigned long long)array % 254 would produce a weighted sum (with truncated range of 0..253). Then removing the value with weight 2 and adding it manually would produce the correct result:
uint64_t a = *(uint64_t *)array;
return (a & ~256) % 254 + ((a>>9) & 2);
Other mechanism to get the weight is to premultiply each binary digit by 255 and masking the correct bit:
uint64_t a = (*(uint64_t *)array * 255) & 0x0102040810204080ULL; // little endian
uint64_t a = (*(uint64_t *)array * 255) & 0x8040201008040201ULL; // big endian
In both cases one can then take the remainder of 255 (and correct now with weight 1):
return (a & 0x00ffffffffffffff) % 255 + (a>>56); // little endian, or
return (a & ~1) % 255 + (a&1);
For the sceptical mind: I actually did profile the modulus version to be (slightly) faster than iteration on x64.
To continue from the answer of JasonD, parallel bit selection can be iteratively utilized.
But first expressing the equation in full form would help the compiler to remove the artificial dependency created by the iterative approach using accumulation:
ret = ((a[0]<<7) | (a[1]<<6) | (a[2]<<5) | (a[3]<<4) |
(a[4]<<3) | (a[5]<<2) | (a[6]<<1) | (a[7]<<0));
vs.
HI=*(uint32_t)array, LO=*(uint32_t)&array[4];
LO |= (HI<<4); // The HI dword has a weight 16 relative to Lo bytes
LO |= (LO>>14); // High word has 4x weight compared to low word
LO |= (LO>>9); // high byte has 2x weight compared to lower byte
return LO & 255;
One more interesting technique would be to utilize crc32 as a compression function; then it just happens that the result would be LookUpTable[crc32(array) & 255]; as there is no collision with this given small subset of 256 distinct arrays. However to apply that, one has already chosen the road of even less portability and could as well end up using SSE intrinsics.
You could use accumulate, with a doubling and adding binary operation:
int doubleSumAndAdd(const int& sum, const int& next) {
return (sum * 2) + next;
}
int decimal = accumulate(array, array+ARRAY_SIZE,
doubleSumAndAdd);
This produces big-endian integers, whereas OP code produces little-endian.
Try this, I converted a binary digit of up to 1020 bits
#include <sstream>
#include <string>
#include <math.h>
#include <iostream>
using namespace std;
long binary_decimal(string num) /* Function to convert binary to dec */
{
long dec = 0, n = 1, exp = 0;
string bin = num;
if(bin.length() > 1020){
cout << "Binary Digit too large" << endl;
}
else {
for(int i = bin.length() - 1; i > -1; i--)
{
n = pow(2,exp++);
if(bin.at(i) == '1')
dec += n;
}
}
return dec;
}
Theoretically this method will work for a binary digit of infinate length
I'm trying to port some Java code, which requires arithmetic and logical bit shifts, to ABAP.
As far as I know, ABAP only supports the bitwise NOT, AND, OR and XOR operations.
Does anyone know another way to implement these kind of shifts with ABAP? Is there perhaps a way to get the same result as the shifts, by using just the NOT, AND, OR and XOR operations?
Disclaimer: I am not specifically familiar with ABAP, hence this answer is given on a more general level.
Assuming that what you said is true (ABAP doesn't support shifts, which I somewhat doubt), you can use multiplications and divisions instead.
Logical shift left (LSHL)
Can be expressed in terms of multiplication:
x LSHL n = x * 2^n
For example given x=9, n=2:
9 LSHL 2 = 9 * 2^2 = 36
Logical shift right (LSHR)
Can be expressed with (truncating) division:
x LSHR n = x / 2^n
Given x=9, n=2:
9 LSHR 2 = 9 / 2^2 = 2.25 -> 2 (truncation)
Arithmetic shift left (here: "ASHL")
If you wish to perform arithmetic shifts (=preserve sign), we need to further refine the expressions to preserve the sign bit.
Assuming we know that we are dealing with a 32-bit signed integer, where the highest bit is used to represent the sign:
x ASHL n = ((x AND (2^31-1)) * 2^n) + (x AND 2^31)
Example: Shifting Integer.MAX_VALUE to left by one in Java
As an example of how this works, let us consider that we want to shift Java's Integer.MAX_VALUE to left by one. Logical shift left can be represented as *2. Consider the following program:
int maxval = (int)(Integer.MAX_VALUE);
System.out.println("max value : 0" + Integer.toBinaryString(maxval));
System.out.println("sign bit : " + Integer.toBinaryString(maxval+1));
System.out.println("max val<<1: " + Integer.toBinaryString(maxval<<1));
System.out.println("max val*2 : " + Integer.toBinaryString(maxval*2));
The program's output:
max value : 01111111111111111111111111111111 (2147483647)
sign bit : 10000000000000000000000000000000 (-2147483648)
max val<<1: 11111111111111111111111111111110 (-2)
max val*2 : 11111111111111111111111111111110 (-2)
The result is negative due that the highest bit in integer is used to represent sign. We get the exact number of -2, because of the way negative numbers are represents in Java (for details, see for instance http://www.javabeat.net/qna/30-negative-numbers-and-binary-representation-in/).
Edit: the updated code can now be found over here: github gist