I'm comparing two NSNumbers in my app and I've done it the wrong way:
if(max < selected)
And it should be:
if([max longValue] < [selected longValue])
So the first comparison is really comparing the two object memory addresses, the funny thing (at least for me) is that the values seems to be related with the addresses. For example, if I get the first number with value 5 its memory address is 0xb000000000000053 and if I get the second with 10 is 0xb0000000000000a3 (being "a" equivalent to 10 in hexadecimal).
For that reason the first comparison (wrong) was actually working. Now an user complaint about an error here and is obviously because of this but it has lead me to the next questions:
Does this only happen in simulators? Cause it's where I'm testing, and the user will have a real device. Or maybe this happen normally but it's not a rule always fulfilled?
This is a "tagged pointer," not an address. The value 5 is packed inside the pointer as you've seen. You can identify tagged pointers because they're odd (the last bit is 1). It's not possible to fetch odd addresses on any of Apple's hardware (the word size is 4 or 8 bytes), so that bit is never set for a real address.
Tagged pointers are only available on 64-bit platforms. If you run on a 32-bit platform then the values will be real pointers, and they may not be in any particular order, which will then lead to the kinds of bugs you're encountering. Unfortunately I don't believe there is any way to get a compiler warning or even a static analysis warning for this kind of misuse on NSNumber.
Mike Ash provides an in-depth discussion of the subject.
On a slightly related note, on 32-bit platforms, certain NSNumbers are singletons, particularly small values since they're used a lot (-1 through 12 as I recall, but I believe it's different on different platforms). This means that == may happen to work for some numbers, but not for others. It also means that without ARC, it was possible to over-release a specific value (for example, 4) such that your program would crash the next time it happened to use that value. True story.... very hard to debug.
Related
I have 93 arrays. Each array has about 18 values in average
I need to make a product of these arrays.
So I have my two dimension array that store these 93 arrays.
Here is what I try to do
DATASET.first.product(*DATASET[1..-1])
Ruby returns
RangeError: too big to product
Does anyone know some workaround to figure out of it?
Some ways to chunk them?
What you want is impossible.
The product of 93 arrays with ~18 elements each is an array with approximately 549975033204266172374216967425209467080301768557741749051999338598022831065169332830885722071173603516904554174087168 elements, each of which is a 93-element array.
This means you need 549975033204266172374216967425209467080301768557741749051999338598022831065169332830885722071173603516904554174087168 * 93 * 64bit of memory to store it, which is roughly 409181424703974032246417423764355843507744515806959861294687507916928986312485983626178977220953161016576988305520852992 bytes. That is about 40 orders of magnitude more than the number of particles in the universe. In other words, even if you were to convert the entire universe into RAM, you would still need to find a way to store on the order of 827180612553027 yobibyte on each and every particle in the universe; that is about 6000000000000000000000000 times the information content of the World Wide Web and 10000000000000000000000 times the information content of the dark web.
Does anyone know some workaround to figure out of it? Some ways to chunk them?
Even if you process them in chunks, that doesn't change the fact that you still need to process 51147678087996754030802177970544480438468064475869982661835938489616123289060747953272372152619145127072123538190106624 elements. Even if you were able to process one element per CPU instruction (which is unrealistic, you will probably need dozens if not hundreds of instructions), and even if each instruction only takes one clock cycle (which is unrealistic, on current mainstream CPUs, each instruction takes multiple clock cycles), and even if you had a terahertz CPU (which is unrealistic, the fastest current CPUs top out at 5 GHz), and even if your CPU had a million cores (which is unrealistic, even GPUs only have a couple of thousand extremely simple cores), and even if your motherboard had a million sockets (which is unrealistic, mainstream motherboards only have a maximum of 4 sockets, and even the biggest supercomputers only have 10 million cores in total), and even if you had a million of those computers in a cluster, and even if you had a million of those clusters in a supercluster, and even if you had a million friends that also have a supercluster like this, it would still take you about 1621000000000000000000000000000000000000000000000000000000000000000000 years to iterate through them.
Right, so as it is hopefully clear that this should not be attempted I'll take a risk and attempt solving your actual problem.
You've mentioned in the comments that you need this array for property testing - I'll take a massive leap of faith here and assume you want to test that every possible combination satisfies some conditions - and this is the mistake here, as the amount of possible combination is just... large...
Instead, you can test that some of the combinations works. You can easily generate a short, randomized list of combinations using:
Array.new(num) { DATASET.map(&:sample) }
Where num is a number of combinations you want to test. Note that there is a chance that some of the entries will be duplicated - but given your dataset size the chances would be comparable with colliding uuids and can be safely ignored.
Generating such a subset of possible solutions is much easier, faster and, most importantly, possible. Since the output is randomized, it will test slightly different combination on each run, so remember to have some randomization setup in your test suite if you want to be able to recreate failures.
I am trying to build a Sieve of Eratosthenes in Lua and i tried several things but i see myself confronted with the following problem:
The tables of Lua are to small for this scenario. If I just want to create a table with all numbers (see example below), the table is too "small" even with only 1/8 (...) of the number (the number is pretty big I admit)...
max = 600851475143
numbers = {}
for i=1, max do
table.insert(numbers, i)
end
If I execute this script on my Windows machine there is an error message saying: C:\Program Files (x86)\Lua\5.1\lua.exe: not enough memory. With Lua 5.3 running on my Linux machine I tried that too, error was just killed. So it is pretty obvious that lua can´t handle the amount of entries.
I don´t really know whether it is just impossible to store that amount of entries in a lua table or there is a simple solution for this (tried it by using a long string aswell...)? And what exactly is the largest amount of entries in a Lua table?
Update: And would it be possible to manually allocate somehow more memory for the table?
Update 2 (Solution for second question): The second question is an easy one, I just tested it by running every number until the program breaks: 33.554.432 (2^25) entries fit in one one-dimensional table on my 12 GB RAM system. Why 2^25? Because 64 Bit per number * 2^25 = 2147483648 Bits which are exactly 2 GB. This seems to be the standard memory allocation size for the Lua for Windows 32 Bit compiler.
P.S. You may have noticed that this number is from the Euler Project Problem 3. Yes I am trying to accomplish that. Please don´t give specific hints (..). Thank you :)
The Sieve of Eratosthenes only requires one bit per number, representing whether the number has been marked non-prime or not.
One way to reduce memory usage would be to use bitwise math to represent multiple bits in each table entry. Current Lua implementations have intrinsic support for bitwise-or, -and etc. Depending on the underlying implementation, you should be able to represent 32 or 64 bits (number flags) per table entry.
Another option would be to use one or more very long strings instead of a table. You only need a linear array, which is really what a string is. Just have a long string with "t" or "f", or "0" or "1", at every position.
Caveat: String manipulation in Lua always involves duplication, which rapidly turns into n² or worse complexity in terms of performance. You wouldn't want one continuous string for the whole massive sequence, but you could probably break it up into blocks of a thousand, or of some power of 2. That would reduce your memory usage to 1 byte per number while minimizing the overhead.
Edit: After noticing a point made elsewhere, I realized your maximum number is so large that, even with a bit per number, your memory requirements would optimally be about 73 gigabytes, which is extremely impractical. I would recommend following the advice Piglet gave in their answer, to look at Jon Sorenson's version of the sieve, which works on segments of the space instead of the whole thing.
I'll leave my suggestion, as it still might be useful for Sorenson's sieve, but yeah, you have a bigger problem than you realize.
Lua uses double precision floats to represent numbers. That's 64bits per number.
600851475143 numbers result in almost 4.5 Terabytes of memory.
So it's not Lua's or its tables' fault. The error message even says
not enough memory
You just don't have enough RAM to allocate that much.
If you would have read the linked Wikipedia article carefully you would have found the following section:
As Sorenson notes, the problem with the sieve of Eratosthenes is not
the number of operations it performs but rather its memory
requirements.[8] For large n, the range of primes may not fit in
memory; worse, even for moderate n, its cache use is highly
suboptimal. The algorithm walks through the entire array A, exhibiting
almost no locality of reference.
A solution to these problems is offered by segmented sieves, where
only portions of the range are sieved at a time.[9] These have been
known since the 1970s, and work as follows
...
I was not able to find why we should have a global innovation number for every new connection gene in NEAT.
From my little knowledge of NEAT, every innovation number corresponds directly with an node_in, node_out pair, so, why not only use this pair of ids instead of the innovation number? Which new information there is in this innovation number? chronology?
Update
Is it an algorithm optimization?
Note: this more of an extended comment than an answer.
You encountered a problem I also just encountered whilst developing a NEAT version for javascript. The original paper published in ~2002 is very unclear.
The original paper contains the following:
Whenever a new
gene appears (through structural mutation), a global innovation number is incremented
and assigned to that gene. The innovation numbers thus represent a chronology of the
appearance of every gene in the system. [..] ; innovation numbers are never changed. Thus, the historical origin of every
gene in the system is known throughout evolution.
But the paper is very unclear about the following case, say we have two ; 'identical' (same structure) networks:
The networks above were initial networks; the networks have the same innovation ID, namely [0, 1]. So now the networks randomly mutate an extra connection.
Boom! By chance, they mutated to the same new structure. However, the connection ID's are completely different, namely [0, 2, 3] for parent1 and [0, 4, 5] for parent2 as the ID is globally counted.
But the NEAT algorithm fails to determine that these structures are the same. When one of the parents scores higher than the other, it's not a problem. But when the parents have the same fitness, we have a problem.
Because the paper states:
In composing the offspring, genes are randomly chosen from veither parent at matching genes, whereas all excess or disjoint genes are always included from the more fit parent, or if they are equally fit, from both parents.
So if the parents are equally fit, the offspring will have connections [0, 2, 3, 4, 5]. Which means that some nodes have double connections... Removing global innovation counters, and just assign id's by looking at node_in and node_out, you avoid this problem.
So when you have equally fit parents, yes you have optimized the algorithm. But this is almost never the case.
Quite interesting: in the newer version of the paper, they actually removed that bolded line! Older version here.
By the way, you can solve this problem by instead of assigning innovation ID's, assign ID based on node_in and node_out using pairing functions. This creates quite interesting neural networks when fitness is equal:
I can't provide a detailed answer, but the innovation number enables certain functionality within the NEAT model to be optimal (like calculating the species of a gene), as well as allowing crossover between the variable length genomes. Crossover is not necessary in NEAT, but it can be done, due to the innovation number.
I got all my answers from here:
http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf
It's a good read
During crossover, we have to consider two genomes that share a connection between the two same nodes in their personal neural networks. How do we detect this collision without iterating both genome's connection genes over and over again for each step of crossover? Easy: if both connections being examined during crossover share an innovation number, they are connecting the same two nodes because they received that connection from the same common ancestor.
Easy Example:
If I am a genome with a specific connection gene with innovation number 'i', my children that take gene 'i' from me may eventually cross over with each other in 100 generations. We have to detect when these two evolved versions (alleles) of my gene 'i' are in collision to prevent taking both. Taking two of the same gene would cause the phenotype to probably loop and crash, killing the genotype.
When I created my first implementation of NEAT I thought the same... why would you keep a innovation number tracker...? and why would you use it only for one generation? Wouldn't be better to not keep it at all and use a key value par with the nodes connected?
Now that I am implementing my third revision I can see what Kenneth Stanley tried to do with them and why he wanted to keep them only for one generation.
When a connection is created, it will start its optimization in that moment. It marks its origin. If the same connection pops out in another generation, that will start its optimization then. Generation numbers try to separate the ones which come from a common ancestor, so the ones that have been optimized for many generations are not put side to side that one that was just generated. If a same connection is found in two genomes, that means that that gene comes from the same origin and thus, can be aligned.
Imagine then that you have your generation champion. Some of their genes will have 50 percent chance to be lost due that the aligned genes are treated equally.
What is better...? I haven't seen any experiments comparing the two approaches.
Kenneth Stanley also addressed this issue in the NEAT users page: https://www.cs.ucf.edu/~kstanley/neat.html
Should a record of innovations be kept around forever, or only for the current
generation?
In my implementation of NEAT, the record is only kept for a generation, but there
is nothing wrong with keeping them around forever. In fact, it may work better.
Here is the long explanation:
The reason I didn't keep the record around for the entire run in my
implementation of NEAT was because I felt that calling something the same
mutation that happened under completely different circumstances was not
intuitive. That is, it is likely that several generations down the line, the
"meaning" or contribution of the same connection relative to all the other
connections in a network is different than it would have been if it had appeared
generations ago. I used a single generation as a yardstick for this kind of
situation, although that is admittedly ad hoc.
That said, functionally speaking, I don't think there is anything wrong with
keeping innovations around forever. The main effect is to generate fewer species.
Conversely, not keeping them around leads to more species..some of them
representing the same thing but separated nonetheless. It is not currently clear
which method produces better results under what circumstances.
Note that as species diverge, calling a connection that appeared in one species a
different name than one that appeared earlier in another just increases the
incompatibility of the species. This doesn't change things much since they were
incompatible to begin with. On the other hand, if the same species adds a
connection that it added in an earlier generation, that must mean some members of
the species had not adopted that connection yet...so now it is likely that the
first "version" of that connection that starts being helpful will win out, and
the other will die away. The third case is where a connection has already been
generally adopted by a species. In that case, there can be no mutation creating
the same connection in that species since it is already taken. The main point is,
you don't really expect too many truly similar structures with different markings
to emerge, even with only keeping the record around for 1 generation.
Which way works best is a good question. If you have any interesting experimental
results on this question, please let me know.
My third revision will allow both options. I will add more information to this answer when I have results about it.
My system needs to store data in an EEPROM flash. Strings of bytes will be written to the EEPROM one at a time, not continuously at once. The length of strings may vary. I want the strings to be saved in order without wasting any space by continuing from the last write address. For example, if the first string of bytes was written at address 0x00~0x08, then I want the second string of bytes to be written starting at address 0x09.
How can it be achieved? I found that some EEPROM's write command does not require the address to be specified and just continues from lastly written point. But EEPROM I am using does not support that. (I am using Spansion's S25FL1-K). I thought about allocating part of memory to track the address and storing the address every time I write, but that might wear out flash faster. What is widely used method to handle such case?
Thanks.
EDIT:
What I am asking is how to track/save the address in a non-volatile way so that when next write happens, I know what address to start.
I never worked with this particular flash, but I've implemented something similar. Unfortunately, without knowing your constrains / priorities (memory or CPU efficient, how often write happens etc.) it is impossible to give a definite answer. Here are some techniques that you may want to consider. I don't know if they are widely used though.
Option 1: Write X bytes containing string length before the string. Then on initialization you could parse your flash: read the length n, jump n bytes forward; read the next byte. If it's empty (all ones for your flash according to the datasheet) then you got your first empty bit. Otherwise you've just read the length of the next string, so do the same over again.
This method allows you to quickly search for the last used sector, since the first byte of the used sector is guaranteed to have a value. The flip side here is overhead of extra n bytes (depending on the max string length) each time you write a string, and having to parse it to get the value (although this can only be done once on boot).
Option 2: Instead of prepending the size, append the unique "end-of-string" sequence, and then parse on boot for the last sequence before ones that represent empty flash.
Disadvantage here is longer parse, but you possibly could get away with just 1 byte-long overhead for each string.
Option 3 would be just what you already thought of: allocating a separate sector that would contain the value you need. To reduce flash wear you could also write these values back-to-back and search for the last one each time you boot. Also, you might consider the expected lifetime of the device that you program versus 100,000 erases that your flash can sustain (again according to the datasheet) - is wearing even a problem? That of course depends on how often data will be saved.
Hope that helps.
Quick question on memory locations in IA-32 assembly language that i cannot seem to find the answer for anywhere else.
On IA-32 each memory address is 4 bytes long (e.g. 0x0040120e). Each of these addresses points to a 1 byte value (or in the case of a larger value, the first byte of it). Now look at these two simple IA-32 assembly language statements:
var1 db 2
var2 db 3
This will place var1 and var2 in adjacent memory cells (let's say 0x0040120e and 0f). Now I realize that the define directive db allocates 1 byte to the value. But, in the case above I have two values (2 and 3) that in fact only requires two bits each, to be stored.
Questions:
When using the db directive, do these two values still consume a full byte, even though they are smaller than 1 byte?
Is using a full byte for values that could get away with less, still the common way to go (as we have so much memory that we don't care)?
Does integers 0 to 255 then generally take up 1 byte and integers 256 to (2^16 - 1) take up 2 bytes (a word), etc.?
Thank you,
Magnus
EDIT 1: Made questions more clear (apologies for the back and forth)
EDIT 2: Added a structured reply below, based on other posters' input
yes. the B in DB is for Byte.
You could use a nibble for each, like so:
combined db 0x23
but you'd have to
a) shift the result for 4 bits right if you need the "2".
b) mask the leftmost 4 bits if you need the "3".
Hardly worth the effort these days ;-)
Yes, since the architecture is byte-addressable and cannot address anything smaller than a byte.
This means that data requiring less than one byte will need to share its address with other data.
In practice this means that you're going to have to know which bits in the pointed-out byte are used for this particular value.
For hardware registers this sort of mapping is very common.
EDIT: Ah, you seem to mean "values of the same variable" when you said "2 and 3". I thought you meant 2-bit and 3-bit values. You need to decide how many bits are needed at most for a particular variable, for all the values you need that variable to be able to store. There are variable-length encodings for integers of course, but that's generally rarely used in assembly and not what you'd typically use for some general-purpose variable.
You generally should expect to reserve all bits required for all values that a variable need to hold, up front. Otherwise, if you're worried about "wasting memory", you would need to move all other variables as soon as you get some "vacant bits" somewhere. That would end up costing fantastically much. Also, knowing the size of a variable is constant makes it possible to generate (or write) the proper code to handle it, otherwise you would of course also need to explicitly store somewhere "the size of the value held in variable x is now y bits". That becomes extremely painful very very quickly.
My initial question was a bit unstructured, so for the benefit of other searchers stopping by here I will use the answers received from #unwind and #geert3 to create a structured response. Again, this was my fault due to the initial poor structuring and creds for the answers goes to #unwind and #geert3.
When using the db directive you allocate 1 byte to the variable, and even if the variable takes up less space than 1 byte, it will still consume that full 1-byte address spot. As one might guess, that wastes a few bits of memory, but that is okay as you have enough memory and not too bothered about wasting a couple of bits. The reason you want to use the full 1-byte memory location is that it is easier to reference the variable when it is alone in the address slot (see #geert3's note on how to access it if you use less than a byte), and additionally, in case you want to reuse the variable later, it is great to know you have space for any number up to 255.
Yes, see answer to 1
Yes, you would normally allocate multiples of a byte to a variable, in a byte-addressable system