I've seen explanations for why RAM is accessed in constant time (O(1)) and why it's accessed in logarithmic time (O(n)). Frankly neither makes much sense to me; what is n in the big-O notation and how does it make sense to measure the speed at which a physical device operates using big-O? I understand an argument for RAM being accessed in linear time is if you have an array a then the kth element would be at address a+k*size_of_type (point is address can be easily calculated). If you know the address of where you want to load or store from, wouldn't that be a constant amount of time in the sense it will always take the same no matter the location? Someone told me looking up something in RAM (like an element in an array) take longer than O(n) because it needs to find the right page. This is wrong as paging pertains to the hard disk, not RAM.
I think it is a nanoseconds value, which is way faster than accessing the disk (5 to 80 ms)
Related
Why is primary and cache memory divided into blocks?
Hi just got posed with this question, I haven't been able to find a detailed explanation corresponding to both primary memory and cache memory, if you have a solution It would be greatly appreciated :)
Thank you
Cache blocks exploit locality of reference based on two types of locality. Temporal locality, after you reference location x you are likely to access location x again shorty. Spatial locality, after you reference location x you are likely to access nearby locations, location x+1, ... shortly.
If you use a value at some distant data center x, you are likely to reuse that value and so it is copied geographically closer, 150ms. If you use a value on disk block x, you are likely to reuse disk block x and so it is kept in memory, 20 ms. If you use a value on memory page x, you are like to reuse memory page x and so the translation of its virtual address to its physical address is kept in the TLB cache. If you use a particular memory location x you are likely to reuse it and its neighbors and so it is kept in cache.
Cache memory is very small, L1D on an M1 is 192kB, and DRAM is very big, 8GB on an M1 Air. L1D cache is much faster than DRAM, maybe 5 cycles vs maybe 200 cycles. I wish this table was in cycles and included registers but it gives a useful overview of latencies:
https://gist.github.com/jboner/2841832
The moral of this is to pack data into aligned structures which fit. If you randomly access memory instead, you will miss in the cache, the TLB, the virtual page cache, ... and everything will be excruciatingly slow.
Most things in computer systems are divided into chunks of fixed sizes: bytes, words, cache blocks, pages.
One reason for this is that while hardware can do many things at once, it is hardware and thus, generally can only do what it was designed for. Making bytes of blocks of 8 bits, making words blocks of 4 bytes (32-bit systems) or 8 bytes (64-bit systems) is something that we can design hardware to do, and mostly in parallel.
Not using fixed-sized chunks or blocks, on the other hand, can make things much more difficult for the hardware, so, data structures like strings — an example of data that is highly variable in length — are usually handled with software loops.
Usually these fixed sizes are in powers of 2 (32, 64, etc..) — because division and modulus, which are very useful operations are easy to do in binary for powers of 2.
In summary, we must subdivide data into blocks because, we cannot treat all the data as one lump sum (hardware wise at least), and, treating all data as individual bits is also too cumbersome. So, we chunk or group data into blocks as appropriate for various levels of hardware to deal with in parallel.
I have just started learning rust, and it is my first proper look into a low level language (I do python, usually). Part of the tutorial explains that a string literal is stored on the stack, because it has a fixed (and known) size; it also explains that a non-initialised string is stored on the heap, so that its size can grow as necessary.
My understanding is that the stack is much faster than the heap. In the case of a string whose size is unknown, but I know it will not ever require more than n bytes, does it make sense to allocate space on the stack for the maximum size, instead of sticking it on the heap?
The purpose of this question is not to solve a problem, but to help me understand, so I would appreciate verbose and detailed answers!
The difference in performance between the stack and the heap comes due to the fact that objects in the heap may change size at run time, and they must then be reallocated somewhere else in the heap.
Now for the verbose part. Imagine you have an integer i32. This number will always be the same size, so any modifications made to it will occur in place. When it goes out of scope (it stops being needed in the program) it will either be deleted, or, a more efficient solution, it will be deleted along with the whole stack it belongs to.
Now you want to create a String. So you create it in the heap and give it a value. And then you modify it and add some characters to it. Now two things can happen.
There is free memory after the string, so the allocator uses this memory to write the new part.
There already is an object allocated in the memory right after the string, and of course, you don't want to overwrite it. So the allocator looks for the next free memory space with enough size to hold the new string and copies into it that string. Then deletes the old one, freeing that memory.
As you can see in the heap the number of operations to be made is incredibly higher than in the stack, so its performance will be lower.
Now, in your case, there are some methods specifically for memory reservation. String::reserve() and String::reserve_exact(). I would recommend you to look at the documentation for Rust always. Usually there already is a std method for what you want.
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.
We are taught that the abstraction of the RAM memory is a long array of bytes. And that for the CPU it takes the same amount of time to access any part of it. What is the device that has the ability to access any byte out of the 4 gigabytes (on my computer) in the same time? As this does not seem as a trivial task for me.
I have asked colleagues and my professors, but nobody can pinpoint to the how this task can be achieved with simple logic gates, and if it isn't just a tricky combination of logic gates, then what is it?
My personal guess is that you could achieve the access of any memory in O(log(n)) speed, where n would be the size of memory. Because each gate would split the memory in two and send you memory access instruction to the next split the memory in two gate. But that requires ALOT of gates. I can't come up with any other educated guess, and I don't even know the name of the device that I should look up in Google.
Please help my anguished curiosity, and thanks in advance.
edit<
This is what I learned!
quote from yours "the RAM can send the value from cell addressed X to some output pins", here is where everyone skip (again) the thing that is not trivial for me. The way that I see it, In order to build a gate that from 64 pins decides which byte out of 2^64 to get, each pin needs to split the overall possible range of memory into two. If bit at index 0 is 0 -> then the address is at memory 0-2^64/2, else address is at memory 2^64/2-2^64. And so on, However the amout of gates (lets call them) that the memory fetch will go through will be 64, (a constant). However the amount of gates needed is N, where N is the number of memory bytes there are.
Just because there is 64 pins, it doesn't mean that you can still decode it into a single fetch from a range of 2^64. Does 4 gigabytes memory come with a 4 gigabytes gates in the memory control???
now this can be improved, because as I read furiously more and more about how this memory is architectured, if you place the memory into a matrix with sqrt(N) rows and sqrt(N) columns, the amount of gates that a fetch memory will need to go through is O(log(sqrt(N)*2) and the amount of gates that will be required will be 2*sqrt(N), which is much better, and I think that its probably a trade secret.
/edit<
What the heck, I might as well make this an answer.
Yes, in the physical world, memory access cannot be constant time.
But it cannot even be logarithmic time. The O(log n) circuit you have in mind ultimately involves some sort of binary (or whatever) tree, and you cannot make a binary tree with constant-length wires in a 3D universe.
Whatever the "bits per unit volume" capacity of your technology is, storing n bits requires a sphere with radius O(n^(1/3)). Since information can only travel at the speed of light, accessing a bit at the other end of the sphere requires time O(n^(1/3)).
But even this is wrong. If you want to talk about actual limitations of our universe, our physics friends say the absolute maximum number of bits you can store in any sphere is proportional to the sphere's surface area, not its volume. So the actual radius of a minimal sphere containing n bits of information is O(sqrt(n)).
As I mentioned in my comment, all of this is pretty much moot. The models of computation we generally use to analyze algorithms assume constant-access-time RAM, which is close enough to the truth in practice and allows a fair comparison of competing algorithms. (Although good engineers working on high-performance code are very concerned about locality and the memory hierarchy...)
Let's say your RAM has 2^64 cells (places where it is possible to store a single value, let's say 8-bit). Then it needs 64 pins to address every cell with a different number. When at the input pins of your RAM there 'appears' a binary number X the RAM can send the value from cell addressed X to some output pins, and your CPU can get the value from there. In hardware the addressing can be done quite easily, for example by using multiple NAND gates (such 'addressing device' from some logic gates is called a decoder).
So it is all happening at the hardware-level, this is just direct addressing. If the CPU is able to provide 64 bits to 64 pins of your RAM it can address every single memory cell (as 64 bit is enough to represent any number up to 2^64 -1). The only reason why you do not get the value immediately is a kind of 'propagation time', so time it takes for the signal to go through all the logic gates in the circuit.
The component responsible for dealing with memory accesses is the memory controller. It is used by the CPU to read from and write to memory.
The access time is constant because memory words are truly layed out in a matrix form (thus, the "byte array" abstraction is very realistic), where you have rows and columns. To fetch a given memory position, the desired memory address is passed on to the controller, which then activates the right column.
From http://computer.howstuffworks.com/ram1.htm:
Memory cells are etched onto a silicon wafer in an array of columns
(bitlines) and rows (wordlines). The intersection of a bitline and
wordline constitutes the address of the memory cell.
So, basically, the answer to your question is: the memory controller figures it out. Of course that, given a memory address, the mapping to column and row must be easy to calculate in a constant time.
To fully understand this topic, I recommend you to read this guide on how memory works: http://computer.howstuffworks.com/ram.htm
There are so many concepts to master that it is difficult to explain it all in one answer.
I've been reading your comments and questions until I answered. I think you are on the right track, but there is some confusion here. The random access in which you are implying doesn't exist in the same way you think it does.
Reading, writing, and refreshing are done in a continuous cycle. A particular cell in memory is only read or written in a certain interval if a signal is detected to do so in that cycle. There is going to be support circuitry that includes "sense amplifiers to amplify the signal or charge detected on a memory cell."
Unless I am misunderstanding what you are implying, your confusion is in how easy it is to read/write to a cell. It's different dependent on chip design but there IS a minimum number of cycles it takes to read or write data to a cell.
These are my sources:
http://www.doc.ic.ac.uk/~dfg/hardware/HardwareLecture16.pdf
http://www.electronics.dit.ie/staff/tscarff/memory/dram_cycles.htm
http://www.ece.cmu.edu/~ece548/localcpy/dramop.pdf
To avoid a humungous answer, I left most of the detail out but all three of these will describe the process you are looking for.
Our teachers has asked us around 50 true of false questions in preparation for our final exam. I could find an answer for most of them online or by asking relative. How ever, those 4 questions adrive driving me crazy. Most of those question aren't that hard, I just cant get any satisfying answer anywhere. Sorry, the original question are not written in english, i had to translate them myself. If you don't understand something, please tell me.
Thanks!
True or false
The size of the manipulated address by the processor determines the size of the virtual memory. How ever, the size of the memory cache is independent.
For long, DRAM technology stayed imcompatible with CMOS technology used to do the standard logic in processor. This is the reason DRAM memory is (most of the time) used outside of the processor (on a different chip).
Pagination let correspond multiple virtual addressing space to a same space of physical addressing.
An associative cache memory with sets of 1 line is an entierly associative cache memory, because one memory block can go in any set since each sets are of the same size that of the block.
"Manipulated address" is not a term of the art. You have an m-bit virtual address mapping to an n-bit physical address. Yes, a cache may be of any size up to the physical address size, but typically is much smaller. Note that cache lines are tagged with virtual or more typically physical address bits corresponding to the maximum virtual or physical address range of the machine.
Yes, DRAM processes and logic processes are each tuned for different objectives, and involve different process steps (different materials and thicknesses to lay down DRAM capacitor stacks/trenches, for example) and historically you haven't built processors in DRAM processes (except the Mitsubishi M32RD) nor DRAM in logic processes. Exception is so-called eDRAM that IBM likes to use for their SOI processes, and which is used as last level cache in IBM microprocessors such as the Power 7.
"Pagination" is what we call issuing a form feed so that text output begins at the top of the next page. "Paging" on the other hand is sometimes a synonym for virtual memory management, by which a virtual address is mapped (on a page by page basis) to a physical address. If you set up your page tables just so it allows multiple virtual addresses (indeed, virtual addresses from different processes' virtual address spaces) to map to the same physical address and hence the same location in real RAM.
"An associative cache memory with sets of 1 line is an entierly associative cache memory, because one memory block can go in any set since each sets are of the same size that of the block."
Hmm, that's a strange question. Let's break it down. 1) You can have a direct mapped cache, in which an address maps to only one cache line. 2) You can have a fully associative cache, in which an address can map to any cache line; there is something like a CAM (content addressible memory) tag structure to find which if any line matches the address. Or 3) you can have an n-way set associative cache, in which you have, essentially, n sets of direct mapped caches, and a given address can map to one of n lines. There are other more esoteric cache organizations, but I doubt you're being taught them.
So let's parse the statement. "An associative cache memory". Well that rules out direct mapped caches. So we're left with "fully associative" and "n-way set associative". It has sets of 1 line. OK, so if it is set associative, then instead of something traditional like 4-ways x 64 lines/way, it is n-ways x 1 lines/way. In other words, it is fully associative. I would say this is a true statement, except the term of the art is "fully associative" not "entirely associative."
Makes sense?
Happy hacking!
True, more or less (it depends on the accuracy of your translation I guess :) ) The number of bits in addresses sets an upper limit on the virtual memory space; you could, of course, choose not to use all the bits. The size of the memory cache depends on how much actual memory is installed, which is independent; but of course if you had more memory than you can address, then it still can't be used.
Almost certainly false. We have RAM on separate chips so that we can install more without building a whole new computer or replacing the CPU.
There is no a-priori upper or lower limit to the cache size, though in a real application certain sizes make more sense than others, of course.
I don't know of any incompatibility. The reason why we use SRAM as on-die cache is because it's faster.
Maybe you can force an MMUs to map different virtual addresses to the same physical location, but usually it's used the other way around.
I don't understand the question.