Synthesizing Shift left by 1 with just NAND gates? - binary

I have an algorithm that performs division of 2 64-bit unsigned integers using C bitwise operators (<<, &, ^, |, ~) in a loop.
Now I would like to eliminate shift left << operator completely to understand how this is done as I can already synthesize AND, OR, XOR, NOT using NAND gates.
Is it possible to perform left shift by 1 with JUST NAND gates too? I have read a little about flip-flops in electronics but I'm implementing this in pure software just to understand it.
I want to avoid using << or >> operators completely and do not want to use existing arithmetic operators from any computer language including assembly.

In hardware, you can implement left shift by 1 without any logic gates at all. Just wire the data lines like so:
If you want something more generic, you could implement a barrel shifter. This can be synthesised from multiplexers:
(source: books24x7.com)
which in turn can be synthesised from NAND gates.
Here is a comprehensive master's thesis on the subject: Barrel Shifter
Design,
Optimization, and
Analysis.

Related

Computing powers of -1

Is there an established idiom for implementing (-1)^n * a?
The obvious choice of pow(-1,n) * a seems wasteful, and (1-2*(n%2)) * a is ugly and not perfectly efficient either (two multiplications and one addition instead of just setting the sign). I think I will go with n%2 ? -a : a for now, but introducing a conditional seems a bit dubious as well.
Making certain assumptions about your programming language, compiler, and CPU...
To repeat the conventional -- and correct -- wisdom, do not even think about optimizing this sort of thing unless your profiling tool says it is a bottleneck. If so, n % 2 ? -a : a will likely generate very efficient code; namely one AND, one test against zero, one negation, and one conditional move, with the AND+test and negation independent so they can potentially execute simultaneously.
Another option looks something like this:
zero_or_minus_one = (n << 31) >> 31;
return (a ^ zero_or_minus_one) - zero_or_minus_one;
This assumes 32-bit integers, arithmetic right shift, defined behavior on integer overflow, twos-complement representation, etc. It will likely compile into four instructions as well (left shift, right shift, XOR, and subtract), with a dependency between each... But it can be better for certain instruction sets; e.g., if you are vectorizing code using SSE instructions.
Incidentally, your question will get a lot more views -- and probably more useful answers -- if you tag it with a specific language.
As others have written, in most cases, readability is more important than performance and compilers, interpreters and libraries are better at optimizing than most people think. Therfore pow(-1,n) * a is likely to be an efficient solution on your platform.
If you really have a performance issue, your own suggestion n%2 ? -a : a is fine. I don't see a reason to worry about the conditional assignment.
If your language has a bitwise AND operator, you could also use n & 1 ? -a : a which should be very efficient even without any optimization. It is likely that on many platforms, this is what pow(a,b) actually does in the special case of a == -1 and b being an integer.

Why bitwise operators are popular in sport programming

I'm a newbie in one of a sport programming service and found that winning solutions often use bitwise operators.
Here is an example.
Write a function, which finds a difference between two
arrays (consider that they differ by one element).
The solutions are:
let s = x => ~eval(x.join`+`);
let findDiff = (a, b) => s(b) - s(a);
and
let findDiff = (a, b) => eval(a.concat(b).join`^`);
I would like to know:
The explanation of those two examples (bitwise part).
What's the advantage of using bitwise operators on decimal numbers?
Is that faster to operate with bitwise operations rather than normal one?
Update:
I didn't fully understand why my question is marked as a duplicate to ~~ vs parseInt. That's good to know, why this operator replaces parseInt and probably helpful for sport programming. But it doesn't answer on my question.
Code golf isn't focused on bitwise operators, is about code length.
Bitwise operators are not necessary faster, but generally fast enough. They are concise (and usually harder to read, but that's side effect).
~~ is a shorter (and usually more preformant) alternative to parseInt with a considerable number of remarks. In regular (non-golf) code it should be used only if it provides the behaviour that is more desirable than parseInt or in performance-sensitive context.
~a is roughly equal to parseInt(a) * -1 - 1. It can be used as a shorter alternative to ~~a in this particular example, s(b) - s(a), because * -1 - 1 part is eliminated on subtraction (the sign should be taken into account).

Expression Trees: Alternatives or Alternate Evaluation Methods

I'm not even sure if this is the right place to ask a question like this.
As a part of my MSc thesis, I am doing some parallel algorithm stuff. To put it simply part of the thing that I am doing is evaluating thousands of expression trees in parallel (expressions like sin(exp (x + y) * cos (z))). What I am doing right now is converting these expression trees to Prefix/Postfix expressions and evaluating them using conventional methods (stack, recursion, etc). These are the basic things that we've all been taught in Data Structures and basic Computer Science courses.
I'm wondering if there is anything else to be used instead of expression trees for dealing with expressions. I know that compilers are heavily using expression trees for parsing phase so I'm assuming there are no alternatives to expression trees (or else someone would have used it in a compiler).
Are there any alternative evaluation methods for such expressions (rather than stacks and recursion). Something more "parallel" friendly? Parsing such expression with stack is sequential and will create a bottleneck in parallel systems. (Exotic/weird/theoretic methods -if any- are also acceptable for my work)
I think that evaluating expression trees is parallelizable, you just don't convert them to the prefix or postfix form.
For example, the tree for the expression you gave would look like this:
sin
|
*
/ \
exp cos
| |
+ z
/ \
x y
When you encounter the *, you could evaluate the exp subexpression on one thread and the cos subexpression on another one. (You could use a future here to make the code simpler, assuming your programming language supports them.)
Although if your expressions really are as simple as this one and you have thousands of them, then I don't see any reason why you would need to evaluate a single expression in parallel. Parallelizing on the expressions themselves should be more than enough (e.g. with 1000 expressions and 2 cores, evaluate 500 on one core and the rest on the other core).

Why do different operators have different associativity?

I've got to the section on operators in The Ruby Programming Language, and it's made me think about operator associativity. This isn't a Ruby question by the way - it applies to all languages.
I know that operators have to associate one way or the other, and I can see why in some cases one way would be preferable to the other, but I'm struggling to see the bigger picture. Are there some criteria that language designers use to decide what should be left-to-right and what should be right-to-left? Are there some cases where it "just makes sense" for it to be one way over the others, and other cases where it's just an arbitrary decision? Or is there some grand design behind all of this?
Typically it's so the syntax is "natural":
Consider x - y + z. You want that to be left-to-right, so that you get (x - y) + z rather than x - (y + z).
Consider a = b = c. You want that to be right-to-left, so that you get a = (b = c), rather than (a = b) = c.
I can't think of an example of where the choice appears to have been made "arbitrarily".
Disclaimer: I don't know Ruby, so my examples above are based on C syntax. But I'm sure the same principles apply in Ruby.
Imagine to write everything with brackets for a century or two.
You will have the experience about which operator will most likely bind its values together first, and which operator last.
If you can define the associativity of those operators, then you want to define it in a way to minimize the brackets while writing the formulas in easy-to-read terms. I.e. (*) before (+), and (-) should be left-associative.
By the way, Left/Right-Associative means the same as Left/Right-Recursive. The word associative is the mathematical perspective, recursive the algorihmic. (see "end-recursive", and look at where you write the most brackets.)
Most of operator associativities in comp sci is nicked directly from maths. Specifically symbolic logic and algebra.

What's the absolute minimum a programmer should know about binary numbers and arithmetic? [closed]

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Although I know the basic concepts of binary representation, I have never really written any code that uses binary arithmetic and operations.
I want to know
What are the basic concepts any
programmer should know about binary
numbers and arithmetic ? , and
In what "practical" ways can binary
operations be used in programming. I
have seen some "cool" uses of shift
operators and XOR etc. but are there
some typical problems where using binary
operations is an obvious choice.
Please give pointers to some good reference material.
If you are developing lower-level code, it is critical that you understand the binary representation of various types. You will find this particularly useful if you are developing embedded applications or if you are dealing with low-level transmission or storage of data.
That being said, I also believe that understanding how things work at a low level is useful even if you are working at much higher levels of abstraction. I have found, for example, that my ability to develop efficient code is improved by understanding how things are represented and manipulated at a low level. I have also found such understanding useful in working with debuggers.
Here is a short-list of binary representation topics for study:
numbering systems (binary, hex, octal, decimal, ...)
binary data organization (bits, nibbles, bytes, words, ...)
binary arithmetic
other binary operations (AND,OR,XOR,NOT,SHL,SHR,ROL,ROR,...)
type representation (boolean,integer,float,struct,...)
bit fields and packed data
Finally...here is a nice set of Bit Twiddling Hacks you might find useful.
Unless you're working with lower level stuff, or are trying to be smart, you never really get to play with binary stuff.
I've been through a computer science degree, and I've never used any of the binary arithmetic stuff we learned since my course ended.
Have a squizz here: http://www.swarthmore.edu/NatSci/echeeve1/Ref/BinaryMath/BinaryMath.html
You must understand bit masks.
Many languages and situations require the use of bit masks, for example flags in arguments or configs.
PHP has its error level which you control with bit masks:
error_reporting = E_ALL & ~E_NOTICE
Or simply checking if an int is odd or even:
isOdd = myInt & 1
I believe basic know-hows on binary operations line AND, OR, XOR, NOT would be handy as most of the programming languages support these operations in the form of bit-wise operators.
These operations are also used in image processing and other areas in graphics.
One important use of XOR operation which I can think of is Parity check. Check this http://www.cs.umd.edu/class/sum2003/cmsc311/Notes/BitOp/xor.html
cheers
The following are things I regularly appreciate knowing in my quite conventional programming work:
Know the powers of 2 up to 2^16, and know that 2^32 is about 4.3 billion. Know them well enough so that if you see the number 2147204921 pop up somewhere your first thought is "hmm, that looks pretty close to 2^31" -- that's a very effective module for your bug radar.
Be able to do simple arithmetic; e.g. convert a hexadecimal digit to a nybble and back.
Have some vague idea of how floating-point numbers are represented in binary.
Understand standard conventions that you might encounter in other people's code related to bit twiddling (flags get ORed together to make composite values and AND checks if one's set, shift operators pack and unpack numbers into different bytes, XOR something twice and you get the same something back, that kind of thing.)
Further knowledge is mostly gravy unless you work with significant performance constraints or do other less common work.
At the absolute bare minimum you should be able to implement a bit mask solution. The tasks associated with bit mask operations should ensure that you at least understand binary at a superficial level.
From the top of my head, here are some examples of where I've used bitwise operators to do useful stuff.
A piece of javascript that needed one of those "check all" boxes was something along these lines:
var check = true;
for(var i = 0; i < elements.length; i++)
check &= elements[i].checked;
checkAll.checked = check;
Calculate the corner points of a cube.
Vec3f m_Corners[8];
void corners(float a_Size){
for(size_t i = 0; i < 8; i++){
m_Corners[i] = a_Size * Vec3f(axis(i, Vec3f::X), axis(i, Vec3f::Y), axis(i, Vec3f::Z));
}
}
float axis(size_t a_Corner, int a_Axis) const{
return ((a_Corner >> a_Axis) & 1) == 1
? -.5f
: +.5f;
}
Draw a Sierpinski triangle
for(int y = 0; y < 512; y++)
for(int x = 0; x < 512; x++)
if(x & y) pixels[x + y * w] = someColor;
else pixels[x + y * w] = someOtherColor;
Finding the next power of two
int next = 1 << ((int)(log(number) / log(2));
Checking if a number is a power of two
bool powerOfTwo = number & (number - 1);
The list can go on and on, but for me these are (except for Sierpinksi) everyday examples. Once you'll understand and work with it though, you'll encounter it in more and more places such as the corners of a cube.
You don't specifically mention (nor rule out!-) floating point binary numbers and arithmetic, so I won't miss the opportunity to flog one of my favorite articles ever (seriously: I sometimes wish I could make passing a strict quiz on it a pre-req of working as a programmer...;-).
The most important thing every programmer should know about binary numbers and arithmetic is : Every number in a computer is represented in some kind of binary encoding, and all arithmetic on a computer is binary arithmetic.
The consequences of this are many:
Floating point "bugs" when doing math with IEEE floating point binary numbers (Which is all numbers in javascript, and quite a few in JAVA, and C)
The upper and lower bounds of representable numbers for each type
The performance cost of multiplication/division/square root etc operations (for embedded systems
Precision loss, and accumulation errors
and more. This is stuff you need to know even if you never do a bitwise xor, or not, or whatever in your life. You'll still run into these things.
This really depends on the language you're using. Recent languages such as C# and Java abstract the binary representation from you -- this makes working with binary difficult and is not usually the best way to do things anyway in these languages.
Middle and low level languages like C and C++, however, require you to understand quite a bit about how the numbers are stored underneath -- especially regarding endianness.
Binary knowledge is also useful when implementing a cross platform protcol of some sort .... for example, on x86 machines, byte order is little endian. but most network protocols want big endian numbers. Therefore you have to realize you need to do the conversion for things to go smoothly. Many RFCs, such as this one -> https://www.rfc-editor.org/rfc/rfc4648 require binary knowledge to understand.
In short, it's completely dependent on what you're trying to do.
Billy3
It's handy to know the numbers 256 and 65536. It's handy to know how two's complement negative numbers work.
Maybe you won't run into a lot of binary. I still use it pretty often, but maybe out of habit.
A good familiarity with bitwise operations should make you more facile with boolean algebra, and I think that's important for every programmer--you want to be able to quickly simplify complex logic expressions.
Absolute minimum is, that "2" is not a binary digit and 10b is smaller than 3.
If you never do low-level programming (like C in embedded systems), never have to use a debugger, and never have to work with real numbers, then I suppose you could get by without knowing binary. But knowing binary will make you a stronger programmer, even if indirectly.
Once you venture into those areas you will need to know binary (and its ``sister'' base, hexadecimal). Without knowing it:
Embedded systems programming would be impossible.
Debugging would be hard because you wouldn't know what you were looking at in memory.
Numerical calculations with decimals would give you answers you don't understand.
I learned to twiddle bits back when c and asm were still used for "mainstream" programming. Although I no longer have much use for that knowledge, I recently used it to solve a real-world business problem.
We use a fax service that posts a message back to us when the fax has been sent or failed after x number of retries. The only way I had to identify the fax was a 15 character field. We wanted to consolidate this into one URL for all of our clients. Before we consolidated, all we had to fit in this field was the FaxID PK (32 bit int) column which we just sent as a string.
Now we had to identify the client (a 4 character code) and the database (32 bit int) underneath the client. I was able to do this using base 64 encoding. Without understanding the binary representation of numbers and characters, I probably would never have even thought of this solution.
Some useful information about the number system.
Binary | base 2
Hexadecimal | base 16
Decimal | base 10
Octal | base 8
These are the most common.
Converting them is faily easy.
112 base 8 = (1 x 8^2) + (2 x 8^1) + (4 x 8^0)
74 base 10 = (7 x 10^1) + (4 x 10^0)
The AND, OR, XOR, and etc. are used in logic gates. Search boolean algebra, something well worth the time knowing.
Say for instance, you have 11001111 base 2 and you want to extract the last four only.
Truth table for AND:
P | Q | R
T | T | T
T | F | F
F | F | F
F | T | F
You can use 11001111 base 2 AND 00111111 base 2 = 00001111 base 2
There are plenty of resources on the internet.