what is TCM memory on ARM processors, is it a dedicated memory which resides next to the processor or just a region of RAM which is configured as TCM??.
if it's a dedicated memory, why can we configure it's location and size?.
TCM, Tightly-Coupled Memory is one (or multiple) small, dedicated memory region that as the name implies is very close to the CPU. The main benefit of it is, that the CPU can access the TCM every cycle. Contrary to the ordinary memory there is no cache involved which makes all memory accesses predictable.
The main use of TCM is to store performance critical data and code. Interrupt handlers, data for real-time tasks and OS control structures are a common example.
if it's a dedicated memory, why can we configure
it's location and size
Making it configurable would just complicate the address decoding for all memory accesses while giving no real benefit over a fixed address range. So it was probably easier and faster to just tie the TCM to a fixed address.
Btw, if you are working on a system that has a TCM and you aren't using it yet, try placing your stack there. That usually gives you some percent of performance gain for free since all stack memory accesses are now single cycle and don't pollute the data-cache anymore.
Related
Multi processor systems perform "real" memory operations (those that influence definitive executions, not just speculative execution) out of order and asynchronously as waiting for global synchronization of global state would needlessly stall all executions nearly all the time. On the other hand, immediately outside each individual core, it seems that the memory system, starting with L1 cache, is purely synchronous, consistent, flat from the allowed behavior point of view (allowed semantics); obviously timing depends on the cache size and behavior.
So on a CPU there on one extreme are named "registers" which are private by definition, and on the other extreme there is memory which is shared; it seems a shame that outside the minuscule space of registers, which have peculiar naming or addressing mode, the memory is always global, shared and globally synchronous, and effectively entirely subject to all fences, even if it's memory used as unnamed registers, for the purpose of storing more data than would fit in the few registers, without a possibility of being examined by other threads (except by debugging with ptrace which obviously stalls, halts, serializes and stores the complete observable state of an execution).
Is that always the case on modern computers (modern = those that can reasonably support C++ and Java)?
Why doesn't the dedicated L1 cache provide register-like semantics for those memory units that are only used by a particular core? The cache must track which memory is shared, no matter what. Memory operations on such local data doesn't have to be stalled when strict global ordering of memory operations are needed, as no other core is observing it, and the cache has the power to stall such external accesses if needed. The cache would just have to know which memory units are private (non globally readable) until a stall of out of order operations, which makes then consistent (the cache would probably need a way to ask the core to serialize operations and publish a consistent state in memory).
Do all CPU stall and synchronize all memory accesses on a fence or synchronizing operation?
Can the memory be used as an almost infinite register resource not subject to fencing?
In practice, a single core operating on memory that no other threads are accessing doesn't slow down much in order to maintain global memory semantics, vs. how a uniprocessor system could be designed.
But on a big multi-socket system, especially x86, cache-coherency (snooping the other socket) is part of what makes memory latency worse for cache misses than on a single-socket system, though. (For accesses that miss in private caches).
Yes, all multi-core systems that you can run a single multi-threaded program on have coherent shared memory between all cores, using some variant of the MESI cache-coherency protocol. (Any exceptions to this rule are considered exotic and have to be programmed specially.)
Huge systems with multiple separate coherency domains that require explicit flushing are more like a tightly-coupled cluster for efficient message passing, not an SMP system. (Normal NUMA multi-socket systems are cache-coherent: Is mov + mfence safe on NUMA? goes into detail for x86 specifically.)
While a core has a cache line in MESI Modified or Exclusive state, it can modify it without notifying other cores about changes. M and E states in one cache mean that no other caches in the system have any valid copy of the line. But loads and stores still have to respect the memory model, e.g. an x86 core still has to commit stores to L1d cache in program order.
L1d and L2 are part of a modern CPU core, but you're right that L1d is not actually modified speculatively. It can be read speculatively.
Most of what you're asking about is handled by a store buffer with store forwarding, allowing store/reload to execute without waiting for the store to become globally visible.
what is a store buffer? and Size of store buffers on Intel hardware? What exactly is a store buffer?
A store buffer is essential for decoupling speculative out-of-order execution (writing data+address into the store buffer) from in-order commit to globally-visible L1d cache.
It's very important even for an in-order core, otherwise cache-miss stores would stall execution. And generally you want a store buffer to coalesce consecutive narrow stores into a single wider cache write, especially for weakly-ordered uarches that can do so aggressively; many non-x86 microarchitectures only have fully efficient commit to cache for aligned 4-byte or wider chunks.
On a strongly-ordered memory model, speculative out-of-order loads and checking later to see if any other core invalidated the line before we're "allowed" to read it is also essential for high performance, allowing hit-under-miss for out-of-order exec to continue instead of one cache miss load stalling all other loads.
There are some limitations to this model:
limited store-buffer size means we don't have much private store/reload space
a strongly-ordered memory model stops private stores from committing to L1d out of order, so a store to a shared variable that has to wait for the line from another core could result in the store buffer filling up with private stores.
memory barrier instructions like x86 mfence or lock add, or ARM dsb ish have to drain the store buffer, so stores to (and reloads from) thread-private memory that's not in practice shared still has to wait for stores you care about to become globally visible.
conversely, waiting for shared store you care about to become visible (with a barrier or a release-store) has to also wait for private memory operations even if they're independent.
the memory is always global, shared and globally synchronous, and
effectively entirely subject to all fences, even if it's memory used
as unnamed registers,
I'm not sure what you mean here. If a thread is accessing private data (i.e., not shared with any other thread), then there is almost no need for memory fence instructions1. Fences are used to control the order in which memory accesses from one core are seen by other cores.
Why doesn't the dedicated L1 cache provide register-like semantics for
those memory units that are only used by a particular execution unit?
I think (if I understand you correctly) what you're describing is called a scratchpad memory (SPM), which is a hardware memory structure that is mapped to the architectural physical address space or has its own physical address space. The software can directly access any location in an SPM, similar to main memory. However, unlike main memory, SPM has a higher bandwidth and/or lower latency than main memory, but is typically much smaller in size.
SPM is much simpler than a cache because it doesn't need tags, MSHRs, a replacement policy, or hardware prefetchers. In addition, the coherence of SPM works like main memory, i.e., it comes into play only when there are multiple processors.
SPM has been used in many commercial hardware accelerators such as GPUs, DSPs, and manycore processor. One example I am familiar with is the MCDRAM of the Knights Landing (KNL) manycore processor, which can be configured to work as near memory (i.e., an SPM), a last-level cache for main memory, or as a hybrid. The portion of the MCDRAM that is configured to work as SPM is mapped to the same physical address space as DRAM and the L2 cache (which is private to each tile) becomes the last-level cache for that portion of MCDRAM. If there is a portion of MCDRAM that is configured as a cache for DRAM, then it would be the last-level cache of DRAM only and not the SPM portion. MCDRAM has a much higher bandwdith than DRAM, but the latency is about the same.
In general, SPM can be placed anywhere in the memory hierarchy. For example, it could placed at the same level as the L1 cache. SPM improves performance and reduces energy consumption when there is no or little need to move data between SPM and DRAM.
SPM is very suitable for systems with real-time requirements because it provides guarantees regarding the maximum latency and/or lowest bandwdith, which is necessary to determine with certainty whether real-time constraints can be met.
SPM is not very suitable for general-purpose desktop or server systems where they can be multiple applications running concurrently. Such systems don't have real-time requirements and, currently, the average bandwdith demand doesn't justify the cost of including something like MCDRAM. Moreover, using an SPM at the L1 or L2 level imposes size constraints on the SPM and the caches and makes difficult for the OS and applications to exploit such a memory hierarchy.
Intel Optance DC memory can be mapped to the physical address space, but it is at the same level as main memory, so it's not considered as an SPM.
Footnotes:
(1) Memory fences may still be needed in single-thread (or uniprocessor) scenarios. For example, if you want to measure the execution time of a specific region of code on an out-of-order processor, it may be necessary to wrap the region between two suitable fence instructions. Fences are also required when communicating with an I/O device through write-combining memory-mapped I/O pages to ensure that all earlier stores have reached the device.
I'm a bit of a noob when it comes to kernel programming, and was wondering if anyone could point me in the right direction for beginning the implementation of memory management in a kernel setting. I am currently working on a toy kernel and am doing a lot of research on the subject but I'm a bit confused on the topic of memory management. There are so many different aspects to it like paging and virtual memory mapping. Is there a specific order that I should implement things or any do's and dont's? I'm not looking for any code or anything, I just need to be pointed in the right direction. Any help would be appreciated.
There are multiple aspects that you should consider separately:
Managing the available physical memory.
Managing the memory required by the kernel and it's data structures.
Managing the virtual memory (space) of every process.
Managing the memory required by any process, i.e. malloc and free.
To be able to manage any of the other memory demands you need to know actually how much physical memory you have available and what parts of it are available to your use.
Assuming your kernel is loaded by a multiboot compatible boot loader you'll find this information in the multiboot header that you get passed (in eax on x86 if I remember correctly) from the boot loader.
The header contains a structure describing which memory areas are used and which are free to use.
You also need to store this information somehow, and keep track of what memory is allocated and freed. An easy method to do so is to maintain a bitmap, where bit N indicates whether the (fixed size S) memory area from N * S to (N + 1) * S - 1 is used or free. Of course you probably want to use more sophisticated methods like multilevel bitmaps or free lists as your kernel advances, but a simple bitmap as above can get you started.
This memory manager usually only provides "large" sized memory chunks, usually multiples of 4KB. This is of course of no use for dynamic memory allocation in style of malloc and free that you're used to from applications programming.
Since dynamic memory allocation will greatly ease implementing advanced features of your kernel (multitasking, inter process communication, ...) you usually write a memory manager especially for the kernel. It provides means for allocation (kalloc) and deallocation (kfree) of arbitrary sized memory chunks. This memory is from pool(s) that are allocated using the physical memory manager from above.
All of the above is happening inside the kernel. You probably also want to provide applications means to do dynamic memory allocation. Implementing this is very similar in concept to the management of physical memory as done above:
A process only sees its own virtual address space. Some parts of it are unusable for the process (for example the area where the kernel memory is mapped into), but most of it will be "free to use" (that is, no actually physical memory is associated with it). As a minimum the kernel needs to provide applications means to allocate and free single pages of its memory address space. Allocating a page results (under the hood, invisible to the application) in a call to the physical memory manager, and in a mapping from the requested page to this newly allocated memory.
Note though that many kernels provide its processes either more sophisticated access to their own address space or directly implement some of the following tasks in the kernel.
Being able to allocate and free pages (4KB mostly) as before doesn't help with dynamic memory management, but as before this is usually handled by some other memory manager which is using these large memory chunks as pool to provide smaller chunks to the application. A prominent example is Doug Lea's allocator. Memory managers like these are usually implemented as library (part of the standard library most likely) that is linked to every application.
This question was asked to one of seniors in a programming interview.
According to me, because the sizes of memory accessed by softwares are increasing, the memory may soon be exhausted. So in this case if we used swapping, it would be inefficient. So we would go for virtual memory because it maps the memory in the disk to the main memory.
But if we can have very huge memory then would virtual memory be of use?
And please tell if the above answer needs some modifications.
Virtual memory is still important. One of the main reasons is that it provides protection. While this could be accomplished with a memory protection unit which provides something similar to x86 segments as opposed to a memory management unit which provides virtual memory, this has problems with the next important things virtual memory provides which are sharing and having things memory mapped. Trying to do something such as a shared memory segment (as in the System V IPC shared memory) is very difficult with just a memory protection unit and similar for memory mapped files. Also if you have only a memory protection unit dynamically increasing the memory space of a process is difficult has you are limited to physically contiguous memory.
In short another way to look at this is virtual memory provides one of the fundamental abstractions that an operating system provides to a process in Unix like systems and in most two tiered privilege level systems. While initial part of this abstraction was to make it appear as if the process had access to more memory than the system might have there are other abstractions that virtual memory provides that aren't overcome by simply having lots of RAM.
As for logical vs virtual while the words can have different meanings for different architectures I recommend this SO question.
I suspect that the questioner was confusing the benefits of logical memory with virtual memory. Under logical memory, each process has its own address space providing protection. In addition, the shared kernel address space is protected from improper accesses by user processes.
In other words, while virtual memory is likely to go away in the future, logical memory translation (often conflated with virtual memory) is likely to stay.
So my understanding is that every process has its own virtual memory space ranging from 0x0 to 0xFF....F. These virtual addresses correspond to addresses in physical memory (RAM). Why is this level of abstraction helpful? Why not just use the direct addresses?
I understand why paging is beneficial, but not virtual memory.
There are many reasons to do this:
If you have a compiled binary, each function has a fixed address in memory and the assembly instructions to call functions have that address hardcoded. If virtual memory didn't exist, two programs couldn't be loaded into memory and run at the same time, because they'd potentially need to have different functions at the same physical address.
If two or more programs are running at the same time (or are being context-switched between) and use direct addresses, a memory error in one program (for example, reading a bad pointer) could destroy memory being used by the other process, taking down multiple programs due to a single crash.
On a similar note, there's a security issue where a process could read sensitive data in another program by guessing what physical address it would be located at and just reading it directly.
If you try to combat the two above issues by paging out all the memory for one process when switching to a second process, you incur a massive performance hit because you might have to page out all of memory.
Depending on the hardware, some memory addresses might be reserved for physical devices (for example, video RAM, external devices, etc.) If programs are compiled without knowing that those addresses are significant, they might physically break plugged-in devices by reading and writing to their memory. Worse, if that memory is read-only or write-only, the program might write bits to an address expecting them to stay there and then read back different values.
Hope this helps!
Short answer: Program code and data required for execution of a process must reside in main memory to be executed, but main memory may not be large enough to accommodate the needs of an entire process.
Two proposals
(1) Using a very large main memory to alleviate any need for storage allocation: it's not feasible due to very high cost.
(2) Virtual memory: It allows processes that may not be entirely in the memory to execute by means of automatic storage allocation upon request. The term virtual memory refers to the abstraction of separating LOGICAL memory--memory as seen by the process--from PHYSICAL memory--memory as seen by the processor. Because of this separation, the programmer needs to be aware of only the logical memory space while the operating system maintains two or more levels of physical memory space.
More:
Early computer programmers divided programs into sections that were transferred into main memory for a period of processing time. As higher level languages became popular, the efficiency of complex programs suffered from poor overlay systems. The problem of storage allocation became more complex.
Two theories for solving the problem of inefficient memory management emerged -- static and dynamic allocation. Static allocation assumes that the availability of memory resources and the memory reference string of a program can be predicted. Dynamic allocation relies on memory usage increasing and decreasing with actual program needs, not on predicting memory needs.
Program objectives and machine advancements in the '60s made the predictions required for static allocation difficult, if not impossible. Therefore, the dynamic allocation solution was generally accepted, but opinions about implementation were still divided.
One group believed the programmer should continue to be responsible for storage allocation, which would be accomplished by system calls to allocate or deallocate memory. The second group supported automatic storage allocation performed by the operating system, because of increasing complexity of storage allocation and emerging importance of multiprogramming.
In 1961, two groups proposed a one-level memory store. One proposal called for a very large main memory to alleviate any need for storage allocation. This solution was not possible due to very high cost. The second proposal is known as virtual memory.
cne/modules/vm/green/defn.html
To execute a process its data is needed in the main memory (RAM). This might not be possible if the process is large.
Virtual memory provides an idealized abstraction of the physical memory which creates the illusion of a larger virtual memory than the physical memory.
Virtual memory combines active RAM and inactive memory on disk to form
a large range of virtual contiguous addresses. implementations usually require hardware support, typically in the form of a memory management
unit built into the CPU.
The main purpose of virtual memory is multi-tasking and running large programmes. It would be great to use physical memory, because it would be a lot faster, but RAM memory is a lot more expensive than ROM.
Good luck!
In modern-day operating systems, memory is available as an abstracted resource. A process is exposed to a virtual address space (which is independent from address space of all other processes) and a whole mechanism exists for mapping any virtual address to some actual physical address.
My doubt is:
If each process has its own address space, then it should be free to access any address in the same. So apart from permission restricted sections like that of .data, .bss, .text etc, one should be free to change value at any address. But this usually gives segmentation fault, why?
For acquiring the dynamic memory, we need to do a malloc. If the whole virtual space is made available to a process, then why can't it directly access it?
Different runs of a program results in different addresses for variables (both on stack and heap). Why is it so, when the environments for each run is same? Does it not affect the amount of addressable memory available for usage? (Does it have something to do with address space randomization?)
Some links on memory allocation (e.g. in heap).
The data available at different places is very confusing, as they talk about old and modern times, often not distinguishing between them. It would be helpful if someone could clarify the doubts while keeping modern systems in mind, say Linux.
Thanks.
Technically, the operating system is able to allocate any memory page on access, but there are important reasons why it shouldn't or can't:
different memory regions serve different purposes.
code. It can be read and executed, but shouldn't be written to.
literals (strings, const arrays). This memory is read-only and should be.
the heap. It can be read and written, but not executed.
the thread stack. There is no reason for two threads to access each other's stack, so the OS might as well forbid that. Moreover, the tread stack can be de-allocated when the tread ends.
memory-mapped files. Any changes to this region should affect a specific file. If the file is open for reading, the same memory page may be shared between processes because it's read-only.
the kernel space. Normally the application should not (or can not) access that region - only kernel code can. It's basically a scratch space for the kernel and it's shared between processes. The network buffer may reside there, so that it's always available for writes, no matter when the packet arrives.
...
The OS might assume that all unrecognised memory access is an attempt to allocate more heap space, but:
if an application touches the kernel memory from user code, it must be killed. On 32-bit Windows, all memory above 1<<31 (top bit set) or above 3<<30 (top two bits set) is kernel memory. You should not assume any unallocated memory region is in the user space.
if an application thinks about using a memory region but doesn't tell the OS, the OS may allocate something else to that memory (OS: sure, your file is at 0x12341234; App: but I wanted to store my data there). You could tell the OS by touching the end of your array (which is unreliable anyways), but it's easier to just call an OS function. It's just a good idea that the function call is "give me 10MB of heap", not "give me 10MB of heap starting at 0x12345678"
If the application allocates memory by using it then it typically does not de-allocate at all. This can be problematic as the OS still has to hold the unused pages (but the Java Virtual Machine does not de-allocate either, so hey).
Different runs of a program results in different addresses for variables
This is called memory layout randomisation and is used, alongside of proper permissions (stack space is not executable), to make buffer overflow attacks much more difficult. You can still kill the app, but not execute arbitrary code.
Some links on memory allocation (e.g. in heap).
Do you mean, what algorithm the allocator uses? The easiest algorithm is to always allocate at the soonest available position and link from each memory block to the next and store the flag if it's a free block or used block. More advanced algorithms always allocate blocks at the size of a power of two or a multiple of some fixed size to prevent memory fragmentation (lots of small free blocks) or link the blocks in a different structures to find a free block of sufficient size faster.
An even simpler approach is to never de-allocate and just point to the first (and only) free block and holds its size. If the remaining space is too small, throw it away and ask the OS for a new one.
There's nothing magical about memory allocators. All they do is to:
ask the OS for a large region and
partition it to smaller chunks
without
wasting too much space or
taking too long.
Anyways, the Wikipedia article about memory allocation is http://en.wikipedia.org/wiki/Memory_management .
One interesting algorithm is called "(binary) buddy blocks". It holds several pools of a power-of-two size and splits them recursively into smaller regions. Each region is then either fully allocated, fully free or split in two regions (buddies) that are not both fully free. If it's split, then one byte suffices to hold the size of the largest free block within this block.