These are my assignments:
Write a program to find the number of address lines in an n Kbytes of memory. Assume that n is always to the power of 2.
Sample input: 2
Sample output: 11
I don't need specific coding help, but I don't know the relation between address lines and memory.
To express in very easy terms, without any bus-multiplexing, the number of bits required to address a memory is the number of lines (address or data) required to access that memory.
Quoting from the Wikipedia article,
a system with a 32-bit address bus can address 232 (4,294,967,296) memory locations.
for a simple example, consider this, you have 3 address lines (A, B, C), so the values which can be formed using 3 bits are
A B C
0 0 0
0 0 1
0 1 0
0 1 1
1 0 0
1 0 1
1 1 0
1 1 1
Total 8 values. So using ABC, you can access any of those eight values, i.e., you can reach any of those memory addresses.
So, TL;DR, the simple relationship is, with n number of lines, we can represent 2n number of addresses.
An address line usually refers to a physical connection between a CPU/chipset and memory. They specify which address to access in the memory. So the task is to find out how many bits are required to pass the input number as an address.
In your example, the input is 2 kilobytes = 2048 = 2^11, hence the answer 11. If your input is 64 kilobytes, the answer is 16 (65536 = 2^16).
Related
I'm doing a hobby OS project and I an trying to get Virtual Memory set up. I had another project in an x86 architecture working with Page Tables but I am now learning ArmV8 now.
Now, I now that the maximum amount of bits used for addressing is 48[1]. The last 12 to 16 bits are used "as-is" to index within the selected region (depending on which granule size is selected[2]).
I just don't understand how we get those intermediate bits. Obviously the documentation is showing that intermediate tables are used[3] but it is quite unclear on how those tables are used.
In the first half of the following image, we see translation of an address with 4k granules and using 38 address bits.
I can't understand this image in the slightest. The "offsets", for example bits 38 to 30 point to an entry in the L1 table. How and where is this table defined ?
What I think is happening is, this a 12+8+8+8 address translation scheme. Starting from the right, 12 bits to find an offset within a 4096 block of memory. Right of that is 8 bits for L3, meaning that L3 indexes 256 blocks of 4096 bytes (1MB). Right of this, L2, has 8 bits also so 256 entries of (256*4096), totalling 256MB per L2 entry. Right of L2 is L1 with also 8 bits, 256 entries of 256MB means the total addressable memory is 64GB of physical RAM.
I don't think this is correct because that would only allow a 1:1 mapping of memory. Each table descriptor needs to carry some access flags and what not. Thus going back to the question of: how are those table defined. Each offset section is 8 bits and that's not enough to contain the address of a translation table.
Anyway, I am completely lost. I would appreciate if someone could give me a "plain english" explanation of how a translation table walk is done ? A graph would be nice but probably too much effort, I'll make one and share if after to help me synthesize the information. Or at least, if someone has one, a link to a good video/guide where the information isn't totally obfuscated ?
Here is the list of materials I have consulted:
https://developer.arm.com/documentation/den0024/a/The-Memory-Management-Unit/Translating-a-Virtual-Address-to-a-Physical-Address
https://forums.raspberrypi.com/viewtopic.php?t=227139
https://armv8-ref.codingbelief.com/en/chapter_d4/d42_4_translation_tables_and_the_translation_proces.html
https://github.com/bztsrc/raspi3-tutorial/blob/master/10_virtualmemory/mmu.c
[1]https://developer.arm.com/documentation/den0024/a/The-Memory-Management-Unit/Translation-tables-in-ARMv8-A
[2]https://developer.arm.com/documentation/den0024/a/The-Memory-Management-Unit/Translation-tables-in-ARMv8-A/Effect-of-granule-sizes-on-translation-tables
[3]https://developer.arm.com/documentation/den0024/a/The-Memory-Management-Unit/Translating-a-Virtual-Address-to-a-Physical-Address
The entire model behind translation tables arises from three values: the size of a translation table entry (TTE), the hardware page size (aka "translation granule"), and the amount of bits used for virtual addressing.
On arm64, TTEs are always 8 bytes. The hardware page size can be one of 4KiB, 16KiB or 64KiB (0x1000, 0x4000 or 0x10000 bytes), depending on both hardware support and runtime configuration. The amount of bits used for virtual addressing similarly depends on hardware support and runtime configuration, but with a lot more complex constraints.
By example
For the sake of simplicity, let's consider address translation under TTBR0_EL1 with no block mappings, no virtualization going on, no pointer authentication, no memory tagging, no "large physical address" support and the "top byte ignore" feature being inactive. And let's pick a hardware page size of 0x1000 bytes and 39-bit virtual addressing.
From here, I find it easiest to start at the result and go backwards in order to understand why we arrived here. So suppose you have a virtual address of 0x123456000 and the hardware maps that to physical address 0x800040000 for you. Because the page size is 0x1000 bytes, that means that for 0 <= n <= 0xfff, all accesses to virtual address 0x123456000+n will go to physical address 0x800040000+n. And because 0x1000 = 2^12, that means the lowest 12 bytes of your virtual address are not used for address translation, but indexing into the resulting page. Though the ARMv8 manual does not use this term, they are commonly called the "page offset".
63 12 11 0
+------------------------------------------------------------+-------------+
| upper bits | page offset |
+------------------------------------------------------------+-------------+
Now the obvious question is: how did we get 0x800040000? And the obvious answer is: we got it from a translation table. A "level 3" translation table, specifically. Let's defer how we found that for just a moment and suppose we know it's at 0x800037000. One thing of note is that translation tables adhere to the hardware page size as well, so we have 0x1000 bytes of translation information there. And because we know that one TTE is 8 bytes, that gives us 0x1000/8 = 0x200, or 512 entries in that table. 512 = 2^9, so we'll need 9 bits from our virtual address to index into this table. Since we already use the lower 12 bits as page offset, we take bits 20:12 here, which for our chosen address yield the value 0x56 ((0x123456000 >> 12) & 0x1ff). Multiply by the TTE size, add to the translation table address, and we know that the TTE that gave us 0x800040000 is written at address 0x8000372b0.
63 21 20 12 11 0
+------------------------------------------------------------+-------------+
| upper bits | L3 index | page offset |
+------------------------------------------------------------+-------------+
Now you repeat the same process over for how you got 0x800037000, which this time came from a TTE in a level 2 translation table. You again take 9 bits off your virtual address to index into that table, this time with an value of 0x11a ((0x123456000 >> 21) & 0x1ff).
63 30 29 21 20 12 11 0
+------------------------------------------------------------+-------------+
| upper bits | L2 index | L3 index | page offset |
+------------------------------------------------------------+-------------+
And once more for a level 1 translation table:
63 40 39 30 29 21 20 12 11 0
+------------------------------------------------------------+-------------+
| upper bits | L1 index | L2 index | L3 index | page offset |
+------------------------------------------------------------+-------------+
At this point, you used all 39 bits of your virtual address, so you're done. If you had 40-bit addressing, then there'd be another L0 table to go through. If you had 38-bit addressing, then we would've taken the L1 table all the same, but it would only span 0x800 bytes instead of 0x1000.
But where did the L1 translation table come from? Well, from TTBR0_EL1. Its physical address is just in there, serving as the root for address translation.
Now, to perform the actual translation, you have to do this whole process in reverse. You start with a translation table from TTBR0_EL1, but you don't know ad-hoc whether it's L0, L1, etc. To figure that out, you have to look at the translation granule and the number of bits used for virtual addressing. With 4KiB pages there's a 12-bit page offset and 9 bits for each level of translation tables, so with 39 bits you're looking at an L1 table. Then you take bits 39:30 of the virtual address to index into it, giving you the address of the L2 table. Rinse and repeat with bits 29:21 for L2 and 20:12 for L3, and you've arrived at the physical address of the target page.
I am reading the book "Artificial Intelligence" by Stuart Russell and Peter Norvig (Chapter 18). The following paragraph is from the decision trees context.
For a wide variety of problems, the decision tree format yields a
nice, concise result. But some functions cannot be represented
concisely. For example, the majority function, which returns true if
and only if more than half of the inputs are true, requires an
exponentially large decision tree.
In other words, decision trees are good for some kinds of functions
and bad for others. Is there any kind of representation that is
efficient for all kinds of functions? Unfortunately, the answer is no.
We can show this in a general way. Consider the set of all Boolean
functions on "n" attributes. How many different functions are in this
set? This is just the number of different truth tables that we can
write down, because the function is defined by its truth table.
A truth table over "n" attributes has 2^n rows, one for each
combination of values of the attributes.
We can consider the “answer” column of the table as a 2^n-bit number
that defines the function. That means there are (2^(2^n)) different
functions (and there will be more than that number of trees, since
more than one tree can compute the same function). This is a scary
number. For example, with just the ten Boolean attributes of our
restaurant problem there are 2^1024 or about 10^308 different
functions to choose from.
What does author mean by "answer" column of the table as a 2^n-bit number that defines the function?
How did author derive (2^(2^n)) different functions?
Please elaborate on above question, preferably with simple example, such as n = 3.
Consider a general truth table for a 3-input function, where the result for each triple is also a Boolean (1 or 0), represented by variables i through 'p':
A B C f(a,b,c)
0 0 0 i
0 0 1 j
0 1 0 k
0 1 1 l
1 0 0 m
1 0 1 n
1 1 0 o
1 1 1 p
We can now represent any function on three variables as an 8-bit number, ijklmnop. For instance, and is 00000001; or is 01111111; one_hot (exactly one input True) is 01101000.
For 3 variables, you have 2^3 bits in the "answer", the complete function definition. Since there are 8 bits in the "answer", there are 2^8 possible functions we can define.
Does that outline the field of comprehension for you?
More detail on an example function
You simply (once you see the pattern) make the eight bits correspond to the entires in the table. For instance, the table for one-hot looks like this:
A B C f(a,b,c)
0 0 0 0
0 0 1 1
0 1 0 1
0 1 1 0
1 0 0 1
1 0 1 0
1 1 0 0
1 1 1 0
Reading down the "answer" column, labeled f(a,b,c), you get the 8-bit sequence 01101000. That 8-bit number is sufficient to completely define the function: the rows listing all the combinations of a, b, c are in a fixed (numerical) sequence.
You can write any such function in a template format:
def and(a, b, c):
and_def = '00000001'
index = 4*a + 2*b + 1*c
return and_def[index]
Now, if we generalize this to any 3-input binary function:
def_bin_func(a, b, c, func_def)
return func_def[4*a + 2*b + 1*c]
If you wish, you can further generalize the template for a list of inputs: concatenate the bits and use that integer as the index into the func_def string.
Does that clear it up?
The following page table is for a system with 16-bit virtual and physical addresses and with 4,096-byte pages. The reference bit is set to 1 when the page has been referenced. Periodically, a thread zeroes out all values of the reference bit.All numbers are provided in decimal.
I want to convert the following virtual addresses (in hexadecimal) to the equivalent physical addresses. Also I want to set the reference bit for the appropriate entry in the page table.
• 0xE12C
• 0x3A9D
• 0xA9D9
• 0x7001
• 0xACA1
I know the answers are but I want to know how can I achieve these answers:
0xE12C → 0x312C
0x3A9D → 0xAA9D
0xA9D9 → 0x59D9
0x7001 → 0xF001
0xACA1 → 0x5CA1
I found and tried This but it did not help me much.
It is given that virtual address is 16 bit long.Hence, there are 2^16 addresses in the virtual address space.
Page Size is given to be 4 KB ( there are 4K (4 * (2 ^ 10) )addresses in a page), so the number of pages will be ( 2^16 ) / ( 2 ^ 12 ) = 2 ^ 4.
To address each page 4 bits are required.
The most significant 4 bits in the virtual address will denote the page number being referred and the remaining 12 bits will be the page offset.
One thing to remember is page size (in the virtual address space ) is always same as the frame size in the main memory. Hence the last 12 bits will remain same in the physical address as that of the virtual address.
To get the frame address in the main memory just use the first 4 bits.
Example: Consider the virtual address 0xACA1
Here A in ACA1 denotes the page number ( 10 ) and corresponding frame no is 5 ( 0101) hence the resulting physical address will be → 0x5CA1.
To translate a virtual address to a physical address (applies ONLY to this homework question), we need to know 2 things:
Page Size
Number of bits for virtual address
In this example: 16-bit system, 4KB page size and physical memory size is 64KB.
First of all we need to determine the number of needed bits to act as offset inside page. log2(Page-Size) = log2(4096) = 12 bits for offset
Out of the 16 bits for virtual address, 12 are for offset, that means each process has 2^4 = 16 virtual pages. Each entry in page table stores the corresponding frame accommodating the page. For example:
Now lets translate!
First of all for ease of work lets convert 0xE12C to binary.
0xE12C = (1110 0001 0010 1100) in base 2
1110 = 14 in decimal
Entry 14 in P.T => Page frame 3.
Lets concatenate it to the 12 offset bits
Answer: (0011 0001 0010 1100) = 0x312C
Another example: 0x3A9D
0x3A9D = 0011 1010 1001 1101
0011 = 3
PageTable[3] = 10
10 in decimal = 1010 in binary
1010 1010 1001 1101 in binary = 0xAA9D
To help you solve this question, we need to get our details right:
16 bit of virtual address space = 2^16 = 65,536 address space
16 bit of physical address space = 2^16 = 65,536 address space
4096 Byte page size determines the offset, which is Log(4096) / Log (2) = 12 bit. This means, 2^12 for Page size
As per #Akash Mahapatra, the offset from virtual address is directly mapped to the offset onto physical address
As such, we now have:
2^16 (16bit) for virtual address - 2^12 (12bit) for offset = 4-bit for pages, or rather total number of pages available.
I won't repeat the calculation for physical since it's the same numbers.
2^4 (4bit) for pages = 16, which correlates to the number of table entries above!
We're getting there... be patient! :)
Memory Address 0xE12C in hex notation is also known to be holding 16-bit of address. (Since it's stated in the question.)
Let's butcher the address now...
We first remove '0x' from the info.
We can convert E12C to binary notation like #Tony Tannous, but I am going to apply a little short-cut.
I simply use a ratio. Well, the address is notated in 4 characters above, and since 16/4 = 4, I can define the first letter as virtual address, while the other 3 are offset address.
With the information, 'E' in hexadecimal format, I need to convert to Decimal = 14. Then I look at your table provided, and I found page frame '3'. Page frame 3 is noted in decimal format, which then need to be converted back to Hexadecimal format... Duh!... which is 3!
So, the Physical address mapping of the virtual memory location of 0xE12C can be found at 0x312C on the physical memory.
You will then go back to the table, and refer to the reference bit column and put a '1' to the row 14.
Apply the same concept for these -
0x3A9D → 0xAA9D
0xA9D9 → 0x59D9
0x7001 → 0xF001
0xACA1 → 0x5CA1
If you notice, the last 3 digits are the same (which determines the offset).
And the 1st of the 4-digits are mapped according to the table:
table entry 3 -> page frame 10 -> hex notation A
table entry A (10) -> page frame 5 -> hex notation 5
table entry 7 -> page frame 15 -> hex notation F
table entry A (10) -> page frame 5 -> hex notation 5
Hope this explanation helps you and others like me! :)
So i have this question in my homework assignment that i have struggling a bit with. I looked over my lecture content/notes and have been able to utilize those to answer the questions, however, i am not 100% sure that i did everything correctly. There are two parts (part C and D) in the question that i was not able to figure out even after consulting my notes and online sources. I am not looking for a solution for those two parts by any means, but it would be greatly appreciated if i could get, at least, a nudge in the right direction in how i can go about solving it.
I know this is a rather large question, however, i hope someone could possibly check my answers and tell me if all my work and methods of looking at this problem is correct. As always, thank you for any help :)
Alright, so now that we have the formalities out of the way,
--------------------------Here is the Question:--------------------------
Suppose a small direct-mapped cache of blocks with 32 blocks is constructed. Each cache block stores
eight 32-bit words. The main memory—which is byte addressable1—is 16,384 bytes in size. 32-bit words are stored
word aligned in memory, i.e., at an address that is divisible by 4.
(a) How many 32-bit words can the memory store (in decimal)?
(b) How many address bits would be required to address each byte of memory?
(c) What is the range of memory addresses, in hex? That is, what are the addresses of the first and last bytes of
memory? I'll give you a hint: memory addresses are numbered starting at 0.
(d) What would be the address of the last word in memory?
(e) Using the cache mapping scheme discussed in the Chapter 5 lecture notes, how many and which address bits
would be used to form the block offset?
(f) How many and which memory address bits would be used to form the cache index?
(g) How many and which address bits would be used to form the tag field for each cache block?
(h) To which cache block (in decimal) would memory address 0x2A5C map to?
(i) What would be the block offset (in decimal) for 0x2A5C?
(j) How many other main memory words would map to the same block as 0x2A5C?
(k) When the word at 0x2A5C is moved into a cache block, what are the memory addresses (in hex) of the other
words which will also be moved into this block? Express your answer as a range, e.g., [0x0000, 0x0200].
(l) The first word of a main memory block that is mapped to a cache block will always be at an address that is
divisible by __ (in decimal)?
(m) Including the V and tag bits of each cache block, what would be the total size of the cache (in bytes)
(n) what would be the size allocated for the data bits (in bytes)?
----------------------My answers and work-----------------------------------
a) memory = 16384 bytes. 16384 bytes into bits = 131072 bits. 131072/32 = 4096 32-bit words
b) 2^14 (main memory) * 2^2 (4 bits/word) = 2^16. take log(base2)(2^16) = 16 bits
c) couldnt figure this part out (would appreciate some input (NOT A SOLUTION) on how i can go about looking at this problem
d)could not figure this part out either :(
e)8 words in each cache line. 8 * 4(2^2 bits/word) = 32 bits in each cache line. log(base2)(2^5) = 5 bits used for block offset.
f) # of blocks = 2^5 = 32 blocks. log(base2)(2^5) = 5 bits for cache index
g) tag = 16 - 5 - 5 - 2(word alignment) = 4 bits
h) 0x2A5C
0010 10100 10111 00
tag index offset word aligned bits
maps to cache block index = 10100 = 0x14
i) maps to block offset = 10111 = 0x17
j) 4 tag bits, 5 block offset = 2^9 other main memory words
k) it is a permutation of the block offsets. so it maps the memory addresses with the same tag and cache index bits and block offsets of 0x00 0x01 0x02 0x04 0x08 0x10 0x11 0x12 0x14 0x18 0x1C 0x1E 0x1F
l)divisible by 4
m) 2(V+tag+data) = 2(1+4+2^3*2^5) = 522 bits = 65.25 bytes
n)data bits = 2^5 blocks * 2^3 words per block = 256 bits = 32 bytes
Part C:
If a memory has M bytes, and the memory is byte addressable, the the memory addresses range from 0 to M - 1.
For your question, this means that memory addresses range from 0 to 16383, or in hex 0x0 to 0x3FFF.
Part D:
Words are 4 bytes long. So given your answer to C, the last word is at:
(0x3FFFF - 3) -> 0x3FFC.
You can see that this is correct because the lowest 2 bits of the address are 0, which must be true of any 4 byte aligned address.
Can anyone explain how to solve these problems step by step
Assume a 2^24 byte memory.
Assume the memory is byte addressable. What is the lowest address and highest address? How many bits are needed for the address?
Assume the memory is word addressable, with a 16 bit word. What is the lowest address and highest address? How many bits are needed for the address?
Assume the memory is word addressable, with a 32 bit word. What is the lowest address and highest address? How many bits are needed for the address?
A byte is 8 bits. If it's byteaddressable, you can't reference an address by anything other than the start of some 8 bits. That is, in a 2^2 byte memory, you have 4 bytes. The lowest address starts at 0 bytes, and the highest address starts at 3 bytes. (0, 1, 2, 3 = 4 bytes total)
If the bytes are contiguous (they are juxtaposed- touching each other rather than spread out) then you can fit all 4 bytes into a 4 byte memory perfectly.
a)
If you have 2^24 bytes then you have 2^(24 + 3) bits because you're doing (2^24 * 2^3) = 2^(24+3). Thus you have 134,217,728 total bits.
The highest address would be one byte before the end, so the address at 2^24 - 1. Note that it's 2^24 - 1 and not 2^27 - 1 because you are addressing it by bytes and not bits. Lowest address would be 0.
Lowest address = 0
Highest address = 2^24 - 1
b)
A word just means a grouping of bytes. A 1-byte word is literally the same thing as a byte, it just implies that the word is some meaningful piece of data, whereas a byte is not necessarily a meaningful piece of data.
A 16-bit word == a 2-byte word because 8 bits are in a byte, thus if you have 2^24 bytes available, you only have a total of 2^23 words.
Lowest address = 0
Highest address = max number of words - 1 = 2^23 - 1.
c)
Same thing as with a 4-byte word instead of 2. Thus:
2^22 bytes available to store words.
Lowest address = 0
Highest address = max number of words - 1 = 2^22 - 1.
Feel free to correct me if you see any errors. Hope I helped.