Use rand_r(unsigned int *state) instead in parallel and concurrent applications.
Sources: man 3 rand [unix command] http://unixhelp.ed.ac.uk/CGI/man-cgi?rand+3
80 karma · joined June 26, 2012
Use rand_r(unsigned int *state) instead in parallel and concurrent applications.
Sources: man 3 rand [unix command] http://unixhelp.ed.ac.uk/CGI/man-cgi?rand+3
This basically means he's running an optimized version of minimax -- essentially, depth first search of game states looking for states that minimize tiles and keep them in line.
At each step, he looks several steps into the future, assigns them each a numerical score, then picks the move that leads to the best outcome.
Iterative deepening means that he evaluates all 1 move options, then all two move options, then all 3 moves options and so on. It increases the chances of finding a good move within a time constraint.
Alpha beta is a "lossless" optimization that allows you to more aggressively prune the tree when you're searching.
"involving a Model Sin Irvine, California, which the "
"Separately,three road fires in"
The cost of rolling out EMV was determined to be greater than the cost credit card companies paying for the increase in fraud and chargebacks out of pocket.
2. Once you've increased the scope beyond the apps on the device, work needs to be done to show the most relevant and useful actions.
3. Enabling flows like:
- Take file from one app, edit in another app, save back over the original file
- Take an email attachment, edit / modify in another app, then reply back on the same thread
4. But there is no reason a third party can't come in and make it happen.
1. No app discovery -- I want to find out about apps that can work with my content.
2. Action curation -- I want to see the actions that other people think are most useful when dealing with my content.
3. No "Return" actions -- eg. The context knowledge necessary to reply to the same message, or overwrite an existing file.
4. Cross device and cross OS: If this is done right, there's no reason for the action to be bound to just one device or even one person.
Furthermore, as others have noted, your post does smack of premature optimization. Without numbers, most of the claims are all pretty meaningless. Judging by number of instructions is no longer a valid metric on any platform on any level of abstraction and hasn't been since the 1980s.
With minor tweaks to the selection of partitions, quick sort can be made O(n lg n). Specifically, if combined with linear time median finding, we can pick perfect partitions every time. (Of course, this algorithm is painfully slow in practice).
All this said, the idea of analytic combinatorics is interesting for a deeper understanding of algorithm performance. It quantifies behavior that good engineers understand is swept under the rug by Big-O notation.
Of course, if you really want good performance, you'll have to understand the algorithm beyond just it's combinatorial properties -- caching locality and coherence, branch mispredictions, function call-overhead etc. play an enormous role when it comes time to really make code fast.
To write fast code, you need the whole picture.
Still, much better than keeping the passwords in VC unprotected, of course.
My preference still is using environment variables so that the secure bits can be fully decoupled from your code, however..
In many modern processor architectures (x86, for example), a cache-coherence protocol is used to ensure that cache lines provide data according to the memory discipline. On x86, that discipline is Total Store Ordering. (See http://en.wikipedia.org/wiki/Memory_ordering).
This means that if two processors are contending for the same value (eg. trying to increment it, set it to true, or even read it), they will force the CPU to invalidate the cache line containing the value on all the other cores, leading to massive scalability bottlenecks. If multiple cores are contending for the same location in memory, whether it's lock free or not, performance will suffer.
More deviously is the case of false sharing, where 2 different values just happen to fall on the same cache line. Even though they don't conflict, the processor must still invalidate the line on every core. Modern compilers do their best to prevent this, but sometimes they need a little help.
The takeaway is this: Don't try to implement your own locks using CAS -- even something as simple as a lock is very hard to get right (performance-wise) when scaling to dozens and hundreds of cores / threads. People have solved this problem (people.csail.mit.edu/mareko/spaa09-scalablerwlocks.pdf). Writing fast concurrent code (especially lock-free code) is a minefield of weird architecture gotchas. Watch your step.
It's definitely a little ironic that what is needed to make a regular grammar makes the language more inconsistent.