Direct Cache mapping – Computer Science Stack Exchange

Let us assume that we have a machine with $2^{24}$ byte-addressable main memory. The cache size is 4096 bytes, and each cache block contains 16 bytes. Assuming a direct mapped cache:
a. How many blocks of main memory do we have?
b. What is the size of the tag, block, and offset fields?
c. To which cache block will the memory address C12AB16 map?
d. Provide another address that would map to the same block in the cache. The
address should be listed in hexadecimal format.

PRECISE DPLL algorithm definition – Computer Science Stack Exchange

I am confused about the precise definition of the DPLL algorithm. Various sources tend to define DPLL differently:

  1. In pages 110-114 of the book Handbook of Satisfiability(Editors: Biere, A., Heule, M., Van Maaren, H., Walsh, T. Feb 2009. Volume 185 of Frontiers in Artificial Intelligence and Applications) it defines it as backtracking + unit propagation.

Also can be accessed from: http://reasoning.cs.ucla.edu/fetch.php?id=97&type=pdf (pages 106-110).

  1. In wikipedia: https://en.wikipedia.org/wiki/DPLL_algorithm#:~:text=In%20logic%20and%20computer%20science,solving%20the%20CNF%2DSAT%20problem.
    it defines it as backtracking + unit propagation + pure literal elimination.

  2. And in original 1962 paper: https://archive.org/details/machineprogramfo00davi/page/n5/mode/2up
    it mentions 3 rules: one-literal clause rule(unit propagation), affirmitive-negative rule(pure literal elimination) and rule for eliminating atomic formulas(creating resolvents).

Therefore, I am looking for a clear and strict definition of DPLL algorithm. Maybe it should be considered as purely backtracking algorithm and unit propagation and pure literal elimination as its extensions? Or maybe unit propagation is essential part of the algorithm and pure literal elimination is considered to be extention..?

computer science – some number theory method can be used to solve this example quickly?

I have extract some notes from my notes:

Images from Notes

one way to found which of four example is uniform function is that try by hand and take some examples. I will search for a method that we can easily infer just the second one has uniform capability. is there any hint or idea to quickly choose the second one instead of try by hand and examples one by one?

python 3.x – Where to invest finances on Data Science Development/Learning Budget?

I picked up data science about 9 months ago

I have been investing about 10 hours a week into improving my skill set since.

I’m keen to continue to learn and demonstrate my skills to potential future employers, so have decided to allocate around £150 to do so

What resources would you recommend (or advise against) for a relative beginner?

These could be anything, including certifications, courses or books

consensus – Raft Implementation – Computer Science Stack Exchange

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Smart String search algorithm – Computer Science Stack Exchange

I’m looking for a solution to search for strings in a large text file. I would like to match strings with as many of those words in close proximity as possible.

For example, if a query is for the string “what is the term for a supreme court justice”

  • “a supreme court justice has lifetime tenure, meaning”
  • “the term of justice in the supreme court is..”

Would be matches in they are in the document being searched.

I’m sure that algorithms for this type of searching already exist, but I don’t know what they are called or exactly what it is that I’m looking for.

Closestpair algorithm – Computer Science Stack Exchange

I very new to programming and computer science.As an intro to CS I’m reading “The Algorithm Design Manual by Steven S. Skiena”.there was this algorithm that I just can’t get my head around:

A different idea might repeatedly connect the closest pair of endpoints
whose connection will not create a problem, such as premature termination of
the cycle. Each vertex begins as its own single vertex chain. After merging
everything together, we will end up with a single chain containing all the points
in it. Connecting the final two endpoints gives us a cycle. At any step during
the execution of this closest-pair heuristic, we will have a set of single vertices
and the end of vertex-disjoint chains available to merge. In pseudocode:
ClosestPair(P )
Let n be the number of points in set P .
For i = 1 to n − 1 do
d = ∞
For each pair of endpoints (s, t) from distinct vertex chains
if dist(s, t) ≤ d then s m = s, t m = t, and d = dist(s, t)
Connect (s m , t m ) by an edge
Connect the two endpoints by an edge

I would really appreciate it if you took the time to explain this alagorithm to me.Thanks in advance. 🙂

career – Mathematical topics in computer science with applications

I just got my master’s degree in mathematics, it was related to abstract algebra. I’m thinking about applying for a doctoral degree, however, I deeply want to study something with an “applied” appeal.

Does anyone know a branch of computer science that can be done by math students but that can still be considered math?

mathematical programming – Mathematics and Computer Science

I just got my master’s degree in mathematics, it was related to abstract algebra. I’m thinking about applying for a doc degree, however, I deeply want to study something with an “applied” appeal. Does anyone know a branch of computer science that can be done by math students but that can still be considered math? I hope my question makes sense.

Existence of pseudorandom generators – Computer Science Stack Exchange

Here is question 16.2 from Arora and Barak’s textbook on computational complexity:

Show that there exists a number $epsilon>0$ and a function $Gcolon {0,1}^*to{0,1}^*$, s.t. $G$ is a $2^{epsilon n}$ pseudorandom generator, as per the definition of PRG, leaving out the computability condition.

Can anyone give me an approach?