Posts Tagged ‘constant’

Unique values generated by expressions of a given complexity

April 5th, 2012 No comments

The majority of integer constants appearing in source code can be represented using a few bits. CPU designers use this characteristic when designing instruction sets, creating so called short-form or quick instructions that perform some operation involving small integer values, e.g., adding a value between 1 and 8 to a register. Writers of code optimizers are always looking for sequences of short-form instructions that are faster/smaller than the longer forms (the INMOS Transputer only had a short form for load immediate).

I have recently been looking at optimizing expressions written for a virtual machine that only supports immediate loads of decimal values between 1 an 9, and binary add/subtract/multiply/divide, e.g., optimizing an expression containing four operators, ((2*7)+9)*4+9 which evaluates to 101, to one containing three operators, (8+9)*6-1 also evaluates to 101. Intermediate results can have fractional values, but I am only interested in expressions whose final result has an integer value (i.e., zero fractional part).

A little thought shows that the value of an expression containing a subexpression whose value includes a fractional value (e.g., 1/3) can always be generated by an expression containing the same or a fewer number of operators and no intermediate fractional value intermediate results (e.g., 9/(1/5) can be generated using 9*5, i.e., the result of any divide operation always has to be an integer if the final result is to be a unique integer. Enumerating the unique set of values generated by expressions containing a given number of operators shows that divide is redundant for expressions containing six of fewer operators and only adds 11 unique values for seven operators (379,073 possibilities without divide)

Removing support for the minus operator only reduces the size of the result set by around 10%. Possibly being worthwhile time saving for expressions containing many operators or searching for an expression whose result value is very large.

There does not appear to be a straightforward (and fast) algorithm that returns the minimal operation expression for a given constant.

I wrote an R program to exhaustively generate all integer values returned by expressions containing up to seven operators. To find out how many different values, integer/real, could be calculated I wrote a maxima program (this represents fractional values using a rational number representation and exceeds 4G byte of storage for expressions containing more than five operators).

The following figure shows the number of different values that can be generated by an expression containing a given number of operators (blue), the number of integer values (black), the number of positive integer values (red), the smallest positive integer that cannot be calculated by an expression containing the given number of operators (green) (circles are for add/subtract/multiply/divide, squares for add/multiply). Any value below a green line is guaranteed to have a solution in the in the given number of operators (or fewer). The blue diamond line is the mean value of a random expression containing the given number of operators.

Information about the values generated by expressions containing the given number of operators.

Limiting the operators to just add/multiply reduces the number of unique value possibilities. The difference increases linearly’ish to around 35% for seven operators.

The following uses colors to show the minimum number of operators needed to generate the given value, 1 is in the bottom left, 100,000 in the top right; red for one operator, yellow for two, green for three and so on.

Colors showing the minimum number of operators needed to generate the given value.

Knowing that N can be calculated using p operators does not mean that N-1 can also be generated using p operators; it is possible to generate 729 using two operators (i.e., 9*9*9), three operators are required to generate 92 and four to generate 417.

Values under the green line (first figure) are known to have solutions in the given number of operators; quickly obtaining the solution is another matter. There is at least a 50/50 chance that a randomly generated expression containing the given number of operators, and producing an integer value, will calculate a value on or below the diamond blue line. The overhead of storing precomputed minimal operator expressions is not that great for small numbers of operators.

Suggestions for a fast/low storage algorithm (random generation + modification through a cost function performs quite well) for large integer values welcome.

Update. Values from the first figure have been accepted by the On-Line Encyclopedia of Integer Sequences as entries: A181898, A181957, A181958, A181959 and A181960.

Assuming compilers are clever enough (part 1)

May 12th, 2009 1 comment

Developers often assume the compiler they use will do all sorts of fancy stuff for them. Is this because they are lazy and happy to push responsibility for parts of the code they write on to the compiler, or do they actually believe that their compiler does all the clever stuff they assume?

An example of unmet assumptions about compiler performance is the use of const in C/C++, final in Java or readonly in other languages. These are often viewed as a checking mechanism, i.e., the developer wants the compiler to check that no attempt is made to, accidentally, change the value of some variable, perhaps via code added during maintenance.

The surprising thing about variables in source code is that approximately 50% of them don’t change once they have been assigned a value (A Theory of Type Qualifiers for C measurements and Automatic Inference of Stationary Fields for Java).

Developers don’t use const/final qualifiers nearly as often as they could. Most modern compilers can deduce if a locally defined variable is only assigned a value once and make use of this fact during optimization. It takes a lot more resources to deduce this information for non-local variables; developers want their compiler to be fast and so implementors don’t won’t them waiting around while whole program analysis is performed.

Why don’t developers make more use of const/final qualifiers? Is this usage, or lack of, an indicator that developers don’t have an accurate grasp of variable usage, or that they don’t see the benefit of using these qualifiers or perhaps they pass responsibility on to the compiler (program size seems to grow sufficiently fast that whole program optimization often consumes more memory than likely to be available; and when are motherboards going to break out of the 4G limit?)