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Binary Solution LSAT Prep Deconstructing the LSAT since.
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So the input is an unsigned short in xilinx? Is that 8 or 16 bits to us sw guys?
And the output is 5 values 0-15 each in a byte? Or you want the 5 values packed into 3 bytes? (I normally think of packed nibbles in a byte when someone mentions binary coded decimal, otherwise the nibble is just regular old binary). Repeated subtraction of powers of 10 is faster if you dont have any hw mult or div.... which AVR is this for? A real small one? Got a target to beat in bytes or cycles?
Any suggestions on how to improve the C++ method (or libraries that do this)? Anything good available for memory mapped files?
REVIEW MIN DEPOSIT AVG RETURNS VISIT BROKER $10 90% VISIT SITE $20 90% VISIT SITE $250 85% VISIT SITE $50 200% VISIT SITE $200 85% VISIT SITE $100 85% VISIT SITE $10 85% VISIT SITE $250 95% VISIT SITE $250 80% - 90% VISIT SITE $250 85% VISIT SITE
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The 60s options are so hot right now because if you can pick correctly from a “one or the other choice” then you can make between 70%-85% returns in literally 60 seconds . It is fast, fun and a bit addicting to see that you can turn a few hundred dollars into a few thousand dollars in short time frames.
I have heard some people saying that the fastest algorithm is Boyer-Moore and some saying that Knuth-Morris-Pratt is actually faster.
Want an example? Take an array [1..99] of byte. Fill it with numbers in the range 1..100 but leave (random) one out. Use each number only once. Sort it. You'll get an array with first N numbers in the same position as the array index ( A[i] = i for all i in 1..N ) and the rest of it will be off by one ( A[i] = i+1 for all i in N+1..99 ). Do you think that binary search is fastest possible search in that case? Of course no - to find a random number (say m ) you only have to check A[m] and A[m-1] . Two lookups, that's all.
It may seem silly to have a section on checking for the end of a file (EOF), but there are a plethora of methods employed by programmers, and improperly checking for the EOF can absolutely cripple performance and introduce mysterious errors and exceptions to your application.
This test stemmed from several projects where the code created dictionary objects or HashSets as in-memory references to see if particular records already existed with the particular string as a key.
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In binary search you split the list into two "sublists" and you only search the sublist that may contain the value. Depending on how large your array is, you could see a speedup if you split the array into more than two splices. You can determine which region of the array you have to search, by keeping an index, that you search first.
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