Performance Counter for DRAM Per-Rank Memory Access - performancecounter

I have an Intel(R) Core(TM) i7-4720HQ CPU # 2.60GHz (Haswell) processor. I need to retrieve the number of accesses to each DRAM rank, over time, to estimate its power consumption. Based on page 261 of the chipset documentation (i.e., Datasheet, volume 2 (M- and H-processor lines)), I could use the 32-bit value in register, RAM—DRAM_ENERGY_STATUS, as a DRAM energy estimation. But I need rank-level energy estimates. I could also use core and offcore DRAM access performance counters to estimate power consumption, but, as mentioned before, I need per-rank statistics. Besides that, they report whole-system stats, while energy is calculated per-rank. They also do not report many DRAM accesses.
Therefore, IMC counters (which are uncore counters) should be the ideal choice. Perf does not support per-rank counters. I tried to use PCM-Memory to access IMC counter information. But /sys/bus/event_source/devices/uncore_imc is not mounted by the kernel (the version is 5.0.0-37-generic) and the tool does not detect the CPU. I tried to access uncore performance counters, manually. Whole-system DRAM access counters are documented, here (They were not documented in the above-mentioned chipset manual). I can retrieve total DRAM read and write accesses using these counters. But, there is no information about channel or rank-level access stats. How can I find the offset associated with these counters? Should I use trial and error?
P.S.: This question is also asked at Intel Software Tuning, Performance Optimization & Platform Monitoring Forum.

The MSR_DRAM_ENERGY_STATUS always reports an estimate of the energy consume by all memory channels. There is no easy way to break it into per-rank energy. This register reports a highly accurate estimate on Haswell.
The 5.0.0-37-generic kernel is an Ubuntu kernel and does support the uncore_imc/data_reads/ and uncore_imc/data_writes/ events on Haswell, which represent a data read CAS command and a data write CAS command from the IMC, respectively. A full cache-line read and a full cache-line write transactions cause a single bursty 64-byte transaction on the memory bus to a single rank. A partial read is also executed as a single full-line read on the bus, but a partial write may require a full line read followed by a full line write due to restrictions in the protocol. Partial writes are generally negligible.
The uncore_imc/data_reads/ and uncore_imc/data_writes/ events occur for requests targeting DRAM memory generated by any unit, not just cores. These names are given by perf and they correspond to UNC_IMC_DRAM_DATA_READS and UNC_IMC_DRAM_DATA_WRITES, respectively, which are mentioned in the Intel article you've cited. The other three events mentioned there allow you count requests (not CAS commands!) for each of the three possible sources separately (GT, IA, and IO). You won't find them listed under /sys/bus/event_source/devices/uncore_imc/events on your old kernel. They are supported in perf starting with mainstream kernel v5.9-rc2.
By the way, PCM does support these events as well, which it uses to report read and write bandwdith over all channels, but you should use the tool pcm.x, not pcm-memory.x, which only works on server processors.
A Haswell H-processor line processor has a single on-die memory controller with two DDR3L 64-bit channels. Each channel can contain zero, one, or two DIMMs with a total capacity of up to 32 GBs over all channels. Moreover, each DIMM can contain up to two ranks, so a single channel can contain anywhere between zero and four ranks. The i7-4720HQ is a high-end mobile processor. You're probably on a laptop with 8 GBs or 16 GBs of memory. If the memory topology was not changed since purchase, it probably has only two 4GB or 8GB DIMMs, one in each channel, with one remaining free slot per channel available for expansion if desired by the user. This means that there are either one or two ranks per channel.
You can approximate the number of accesses to each rank given the knowledge of how physical addresses are mapped to ranks. If each channel is populated with a single rank DIMM of the same capacity, the mapping is simple on your processor. Bit 6 of the physical address (i.e., the seventh bit) determines which channel, and therefore which rank, a request is mapped to. You can collect a set of samples of physical addresses of requests at the IMC by running perf record on MEM_LOAD_UOPS_L3_MISS_RETIRED.LOCAL_DRAM with the --phys-data option. Obviously this set of samples may only be representative of core-originated retired loads that reach the IMC, which are a small subset of all requests at the IMC.
It appears to me that you want to measure the number of memory accesses per rank in order to estimate the the per-rank energy from the total DRAM energy, but this is not trivial at all for the following reasons:
Not all CAS commands are of the same energy cost. Precharge and activate commands are not counted by any event and may consume significant energy, especially with high row buffer miss rates.
Even if there are zero requests in the IMC, as long as there is at least one active core, the memory channels are powered and do consume energy.
The amount of time it takes to process a request of the same type and to the same address may vary depending surrounding requests due to timing delays required by rank-to-rank turnarounds and read-write switching.
Despite of all of that, I imagine it may be possible to build a good model of upper and lower bounds on per-rank energy given a representative estimate of the number of requests to each rank (as discussed above).
The bottom line is that there is no easy way to get the luxury of per-rank counting like on server processors.

Related

Is there any connection between the segments created in memory by a microprocessor and the memory structure of a process in an operating system?

In 8086 microprocessor, we segment the memory into segments of 64K each because of the 16 bit registers (Since a 20 bit address cannot be stored in the 16 bit register). These segments are categorized as code segment, data segment, stack segment and extra segment. This structure is similar to that of created by a process in operating system. Does that mean each process takes up memory equivalent to 4 segments which will be equivalent to 4*64K in case of 8086 ? And if this is true then by doing some more math we can say that only 4 process will be handled by a 8086 microprocessor at a time (i.e. one of the process will be running state and others would be in block or ready state) since maximum of 16 segments are possible (Total memory size / size of each segment = 1MB/64K = 16).
I have just started studying this and saw this equivalence between process and segments. Does any such connection between the segments of the memory and the memory structure of the process actually exists or it's just my crazy imagination ?
A little history helps. Early UNIX(tm) ran on the Digital pdp minicomputer family. The first circulated versions were V6 & V7, which were exclusive to the pdp-11 family. That family could support a whopping 256K of RAM; but the gp register set (used for address formation) were 16bits wide. There was a limited memory protection scheme in the processor, which permitted the kernel (supervisor) to have a separate address space from user (user); and instructions (addresses generated by pc) to be separate from data (generated by other means). This will probably get edited into the dust by pdp-11 fanbois.
At around this time, intel was rolling what was to become the 8086. Current 8-bit CPUs were already straining at a 64K address space limitation, and were using a concept called bank switching to increase that. In bank switching, some sub-ranges of the 64K address space could be re-pointed into a larger memory bank; so although you could carefully address much more memory. The Hitachi 64180 was one of the CPUs that incorporated this into its silicon; most used external memory controllers.
The 8086 addressing scheme was an amalgamation of these notions. You could produce an Operating System which supported dynamically relocated processes and shared text with up to 64K Instruction + 64K Data. The general idea was you take the segment registers out of the programming model, thus if the OS has to relocate the process, it knows that the process had no saved copy of the old segment value. The commercial OS QNX 1.x, 2.x provided this as a model; the later using the 286 extensions to protect against programs that played with the segment registers.
For programs that didn't care about such subtleties (Lotus 123, ...), you could use the segment registers to effectively create a 2^20 address space on the 8086. It is an ugly programming model in this mode because address formation is A=Seg*16+Base, so Seg=1,Base=0 and Seg=0,Base=16 resolve to the same address.
So, you aren't hallucinating, it was quite intentional, if more than a little half-arsed.

Query amount of VRAM or GPU clock speed

I am writing code to pick a physical device, but I want to put in some logic to prefer newer devices (more VRAM or higher clock speed) in case multiple ones fit my minimum feature requirements.
Is this possible?
Vulkan has no specific API calls to get such GPU details, for that you'd need to go with vendor specific APIs like NVAPI. The only hint may be deviceType member of VkPhysicalDeviceProperties that returns whether it's an integraed, discrete or virtual GPU.
The VRAM size though can be determined by finding the memory heap with the DEVICE_LOCAL bit set using vkGetPhysicalDeviceMemoryProperties. The VkPhysicalDeviceMemoryProperties returned by that function contains all available memory heaps in the memoryHeaps member. The configuration differs esp. between discrete and integrated GPUs, so this may not always be what you're looking for, e.g. on integrated GPUs with shared memory.
Heaps for a discrete GPU: http://vulkan.gpuinfo.org/displayreport.php?id=1432#memoryheaps
Heaps for an integrated GPU: http://vulkan.gpuinfo.org/displayreport.php?id=1200#memoryheaps

Max size of thread local memory of a GPU thread (C++ AMP)

I'd like to create an integer array of 100 and an another one of ~10-100 integers (varies by user input) on every thread. I will reuse the data in the array_views several times on a thread so I want to copy the content of the aray view as local data to enhance memory access time. (Every thread is responsible for its "own" 100 elements of the array_view, creating one thread for every element is not possible with my algorythm) If it is not possible, tile static memory will do the trick too, but the thread local one would be better.
My question is, how many bytes can I allocate on a thread as local variable/array(a minimum amount which will work on most GPU s)?
Also, with which software can I query the capabilites of my GPU (Number of registers per thread, size of static memory per tile, etc.) The CUDA SDK has an utility app which queries the capabilities of the GPU, but I have an AMD one, Radeon HD 5770, and it won't work with my GPU if I am correct.
Opencl api can query gpu or cpu devices for capabilities of opencl programs but results should be similar for any natively optimized structure. But if your C++ AMP is based on HLSL or similar, you may not be able to use LDS.
32kB LDS and 24kB constant cache per compute unit means you can have 1kB LDS + 0.75kB per thread when you choose 32 threads per compute unit. But drivers may use some of it for other purposes, you can always test for different sizes. Look at constant cache bandwidth, its 2x performance of LDS bw.
If you are using those arrays without sharing with oter threads (or without any synchronization), you can use 256kB register space per compute unit(8kB per thread (setup of 32 threads per cu)) with six times wider bandwidth than LDS. But there are always some limits so actual usable value may be half of this.
taken from appendix - d of http://developer.amd.com/wordpress/media/2013/07/AMD_Accelerated_Parallel_Processing_OpenCL_Programming_Guide-rev-2.7.pdf

How to leverage blocks/grid and threads/block?

I'm trying to accelerate this database search application with CUDA, and I'm working on running a core algorithm in parallel with CUDA.
In one test, I run the algorithm in parallel across a digital sequence of size 5000 with 500 blocks per grid and 100 threads per block and came back with a runt time of roughly 500 ms.
Then I increased the size of the digital sequence to 8192 with 128 blocks per grid and 64 threads per block and somehow came back with a result of 350 ms to run the algorithm.
This would indicate that how many blocks and threads used and how they're related does impact performance.
My question is how to decide the number of blocks/grid and threads/block?
Below I have my GPU specs from a standard device query program:
You should test it because it depends on your particular kernel. One thing you must aim to do is to make the number of threads per block a multiple of the number of threads in a warp. After that you can aim for high occupancy of each SM but that is not always synonymous with higher performance. It was been shown that sometimes lower occupancy can give better performance. Memory bound kernels usually benefit more from higher occupancy to hide memory latency. Compute bound kernels not so much. Testing the various configurations is your best bet.

Are disk sector writes atomic?

Clarified Question:
When the OS sends the command to write a sector to disk is it atomic? i.e. Write of new data succeeds fully or old data is left intact should the power fail immediately following the write command. I don't care about what happens in multiple sector writes - torn pages are acceptable.
Old Question:
Say you have old data X on disk, you write new data Y over it, and a tree falls on the power line during that write. With no fancy UPS or battery backed disk controller, you can end up with a torn page, where the data on disk is part X and part Y. Can you ever end up with a situation where the data on disk is part X, part Y, and part garbage?
I've been trying to understand the design of ACID systems like databases, and to my naive thinking, it seems firebird, which does not use a write-ahead log, is relying that a given write will not destroy old data (X) - only fail to fully write new data (Y). That means that if part of X is being overwritten, only the part of X that is being overwritten can be changed, not the part of X we intend to keep.
To clarify, this means if you have a page sized buffer, say 4096 bytes, filled with half Y, half X that we want to keep - and we tell the OS to write that buffer over X, there is no situation short of serious disk failure where the half X that we want to keep is corrupted during the write.
The traditional (SCSI, ATA) disk protocol specifications don't guarantee that any/every sector write is atomic in the event of sudden power loss (but see below for discussion of the NVMe spec). However, it seems tacitly agreed that non-ancient "real" disks quietly try their best to offer this behaviour (e.g. Linux kernel developer Christoph Hellwig mentions this off-hand in the 2017 presentation "Failure-Atomic file updates for Linux").
When it comes to synthetic disks (e.g. network attached block devices, certain types of RAID etc.) things are less clear and they may or may not offer sector atomicity guarantees while legally behaving per their given spec. Imagine a RAID 1 array (without a journal) comprised of a disk that offers 512 byte sized sectors but where the other disk offered a 4KiB sized sector thus forcing the RAID to expose a sector size of 4KiB. As a thought experiment, you can construct a scenario where each individual disk offers sector atomicity (relative to its own sector size) but where the RAID device does not in the face of power loss. This is because it would depend on whether the 512 byte sector disk was the one being read by the RAID and how many of the 8 512-byte sectors compromising the 4KiB RAID sector it had written before the power failed.
Sometimes specifications offer atomicity guarantees but only on certain write commands. The SCSI disk spec is an example of this and the optional WRITE ATOMIC(16) command can even give a guarantee beyond a sector but being optional it's rarely implemented (and thus rarely used). The more commonly implemented COMPARE AND WRITE is also atomic (potentially across multiple sectors too) but again it's optional for a SCSI device and comes with different semantics to a plain write...
Curiously, the NVMe spec was written in such a way to guarantee sector atomicity thanks to Linux kernel developer Matthew Wilcox. Devices that are compliant with that spec have to offer a guarantee of sector write atomicity and may choose to offer contiguous multi-sector atomicity up to a specified limit (see the AWUPF field). However, it's unclear how you can discover and use any multi-sector guarantee if you aren't currently in a position to send raw NVMe commands...
Andy Rudoff is an engineer who talks about investigations he has done on the topic of write atomicity. His presentation "Protecting SW From Itself: Powerfail Atomicity for Block Writes" (slides) has a section of video where he talks about how power failure impacts in-flight writes on traditional storage. He describes how he contacted hard drive manufacturers about the statement "a disk's rotational energy is used to ensure that writes are completed in the face of power loss" but the replies were non-committal as to whether that manufacturer actually performed such an action. Further, no manufacturer would say that torn writes never happen and while he was at Sun, ZFS added checksums to blocks which led to them uncovering cases of torn writes during testing. It's not all bleak though - Andy talks about how sector tearing is rare and if a write is interrupted then you usually get only the old sector, or only the new sector, or an error (so at least corruption is not silent). Andy also has an older slide deck Write Atomicity and NVM Drive Design which collects popular claims and cautions that a lot of software (including various popular filesystems on multiple OSes) are actually unknowingly dependent on sector writes being atomic...
(The following takes a Linux centric view but many of the concepts apply to general-purpose OSes that are not being deployed in a tightly controlled hardware environments)
Going back to 2013, BtrFS lead developer Chris Mason talked about how (the now defunct) Fusion-io had created a storage product that implemented atomic operation (Chris was working for Fusion-io at the time). Fusion-io also created a proprietary filesystem "DirectFS" (written by Chris) to expose this feature. The MariaDB developers implemented a mode that could take advantage of this behaviour by no longer doing double buffering resulting in "43% more transactions per second and half the wear on the storage device". Chris proposed a patch so generic filesystems (such as BtrFS) could advertise that they provided atomicity guarantees via a new flag O_ATOMIC but block layer changes would also be needed. Said block layer changes were also proposed by Chris in a later patch series that added a function blk_queue_set_atomic_write(). However, neither of the patch series ever entered the mainline Linux kernel and there is no O_ATOMIC flag in the (current 2020) mainline 5.7 Linux kernel.
Before we go further, it's worth noting that even if a lower level doesn't offer an atomicity guarantee, a higher level can still provide atomicity (albeit with performance overhead) to its users so long as it knows when a write has reached stable storage. If fsync() can tell you when writes are on stable storage (technically not guaranteed by POSIX but the case on modern Linux) then because POSIX rename is atomic you can use the create new file/fsync/rename dance to do atomic file updates thus allowing applications to do double buffering/Write Ahead Logging themselves. Another example lower down in the stack are Copy On Write filesystems like BtrFS and ZFS. These filesystems give userspace programs a guarantee of "all the old data" or "all the new data" after a crash at sizes greater than a sector because of their semantics even though a disk many not offer atomic writes. You can push this idea all the way down into the disk itself where NAND based SSDs don't overwrite the area currently used by an existing LBA and instead write the data to a new region and keep a mapping of where the LBA's data is now.
Resuming our abridged timeline, in 2015 HP researchers wrote a paper Failure-Atomic Updates of Application Data
in a Linux File System (PDF) (media) about introducing a new feature into the Linux port of AdvFS (AdvFS was originally part of DEC's Tru64):
If a file is opened with a new O_ATOMIC flag, the state of its application data will always reflect the most recent successful msync, fsync, or fdatasync. AdvFS furthermore includes a new syncv operation that combines updates to multiple files into a failure-atomic bundle [...]
In 2017, Christoph Hellwig wrote experimental patches to XFS to provide O_ATOMIC. In the "Failure-Atomic file updates for Linux" talk (slides) he explains how he drew inspiration from the 2015 paper (but without the multi-file support) and the patchset extends the XFS reflink work that already existed. However, despite an initial mailing list post, at the time of writing (mid 2020) this patchset is not in the mainline kernel.
During the database track of the 2019 Linux Plumbers Conference, MySQL developer Dimitri Kravtchuk asked if there were plans to support O_ATOMIC (link goes to start of filmed discussion). Those assembled mention the XFS work above, that Intel claim they can do atomicity on Optane but Linux doesn't provide an interface to expose it, that Google claims to provide 16KiB atomicity on GCE storage1. Another key point is that many database developers need something larger than 4KiB atomicity to avoid having to do double writes - PostgreSQL needs 8KiB, MySQL needs 16KiB and apparently the Oracle database needs 64KiB. Further, Dr Richard Hipp (author of the SQLite database) asked if there's a standard interface to request atomicity because today SQLite makes use of the F2FS filesystem's ability to do atomic updates via custom ioctl()s but the ioctl was tied to one filesystem. Chris replied that for the time being there's nothing standard and nothing provides the O_ATOMIC interface.
At the 2021 Linux Plumbers Conference Darrick Wong re-raised the topic of atomic writes (link goes to start of filmed discussion). He pointed out there are two different things that people mean when they say they want atomic writes:
Hardware provides some atomicity API and this capability is somehow exposed through the software stack
Make the filesystem do all the work to expose some sort of atomic write API irrespective of hardware
Darrick mentioned that Christoph had ideas for 1. in the past but Christoph has not come back to the topic and further there are unanswered questions (how you make userspace aware of limits, if the feature was exposed it would be restricted to direct I/O which may problematic for many programs). Instead Darrick suggested tackling 2. was to propose his FIEXCHANGE_RANGE ioctl which swaps the contents of two files (the swap is restartable if it fails part way through). This approach doesn't have the limits (e.g. smallish contiguous size, maximum number of scatter gather vectors, direct I/O only) that a hardware based solution would have and could theoretically be implementable in the VFS thus being filesystem agnostic...
TLDR; if you are in tight control of your whole stack from application all the way down the the physical disks (so you can control and qualify the whole lot) you can arrange to have what you need to make use of disk atomicity. If you're not in that situation or you're talking about the general case, you should not depend on sector writes being atomic.
When the OS sends the command to write a sector to disk is it atomic?
At the time of writing (mid-2020):
When using a mainline 4.14+ Linux kernel
If you are dealing with a real disk
a sector write sent by the kernel is likely atomic (assuming a sector is no bigger than 4KiB). In controlled cases (battery backed controller, NVMe disk which claims to support atomic writes, SCSI disk where the vendor has given you assurances etc.) a userspace program may be able to use O_DIRECT so long as O_DIRECT wasn't reverting to being buffered, the I/O didn't get split apart/merged at the block layer / you are sending device specific commands and are bypassing the block layer. However, in the general case neither the kernel nor a userspace program can safely assume sector write atomicity.
Can you ever end up with a situation where the data on disk is part X, part Y, and part garbage?
From a specification perspective if you are talking about a SCSI disk doing a regular SCSI WRITE(16) and a power failure happening in the middle of that write then the answer is yes: a sector could contain part X, part Y AND part garbage. A crash during an inflight write means the data read from the area that was being written to is indeterminate and the disk is free to choose what it returns as data from that region. This means all old data, all new data, some old and new, all zeros, all ones, random data etc. are all "legal" values to return for said sector. From an old draft of the SBC-3 spec:
4.9 Write failures
If one or more commands performing write operations are in the task set and are being processed when power is lost (e.g., resulting in a vendor-specific command timeout by the application client) or a medium error or hardware error occurs (e.g., because a removable medium was incorrectly unmounted), the data in the logical blocks being written by those commands is indeterminate. When accessed by a command performing a read or verify operation (e.g., after power on or after the removable medium is mounted), the device server may return old data, new data, or vendor-specific data in those logical blocks.
Before reading logical blocks which encountered such a failure, an application client should reissue any commands performing write operations that were outstanding.
1 In 2018 Google announced it had tweaked its cloud SQL stack and that this allowed them to use 16k atomic writes MySQL's with innodb_doublewrite=0 via O_DIRECT... The underlying customisations Google performed were described as being in the virtualized storage, kernel, virtio and the ext4 filesystem layers. Further, a no longer available beta document titled Best practices for 16 KB persistent disk and MySQL (archived copy) described what end users had to do to safely make use of the feature. Changes included: using an appropriate Google provided VM, using specialized storage, changing block device parameters and carefully creating an ext4 filesystem with a specific layout. However, at some point in 2020 this document vanished from GCE's online guides suggesting such end user tuning is not supported.
I think torn pages are not the problem. As far as I know, all drives have enough power stored to finish writing the current sector when the power fails.
The problem is that everybody lies.
At least when it comes to the database knowing when a transaction has been committed to disk, everybody lies. The database issues an fsync, and the operating system only returns when all outstanding writes have been committed to disk, right? Maybe not. It's common, especially with RAID cards and/or SATA drives, for your program to be told everything has committed (that is, fsync returns) and yet there is data not yet on the drive.
You can try using Brad's diskchecker to find out if the platform you are going to use for your database can survive pulling the plug without losing data. The bottom line: If diskchecker fails, the platform is not safe for running a database. Databases with ACID rely upon knowing when a transaction has been committed to backing store and when it has not. This is true whether or not the databases uses write-ahead loggin (and if the database returns to the user without having done an fsync, then transactions can be lost in the event of a failure, so it should not claim that it provides ACID semantics).
There's a long thread on the Postgresql mailing list discussing durability. It starts out talking about SSDs, but then it gets into SATA drives, SCSI drives, and file systems. You may be surprised to learn how exposed your data can be to loss. It's a good thread for anyone with a database that needs durability, not just those running Postgresql.
Nobody seems to agree on this question. So I spent a lot of time trying different Google queries until I finally found an answer.
from Dr. Stephen Tweedie, RedHat employee and linux kernel filesystem and virtual memory developer in a talk on ext3 (which he developed) transcript here. If anyone knows, it'd be him.
"It's not sufficient just to write the thing to the journal, because there's got to be some mark in the journal which says: well, (has this journal record actually) does this journal record actually represent a complete consistency to the disk? And the way you do that is by having some atomic operation which marks that transaction as being complete on disk" [23m, 14s]
"Now, disks these days actually make these guarantees. If you start a write operation to a disk, then even if the power fails in the middle of that sector write, the disk has enough power available, and it can actually steal power from the rotational energy of the spindle; it has enough power to complete the write of the sector that's being written right now. In all cases, the disks make that guarantee." [23m, 41s]
No, they are not. Worse yet, disks may lie and say the data is written when it is in fact in the disk cache, under default settings. For performance reasons, this may be desirable (actual durability is up to an order of magnitude slower) but it means if you lose power and the disk cache is not physically written, your data is gone.
Real durability is both hard and slow unfortunately, since you need to make at least one full rotation per write, or 2+ with journalling/undo. This limits you to a couple hundred DB transactions per second, and requires disabling write caching at a fairly low level.
For practical purposes though, the difference is not that big of a deal in most cases.
See:
How (not) to achieve durability.
FSync() may not flush to disk
People don't seem to agree on what happens during a sector write if the power fails. Maybe because it depends on the hardware being used, and even the filesystem.
From wikipedia (http://en.wikipedia.org/wiki/Journaling_file_system):
Some disk drives guarantee write
atomicity during a power failure.
Others, however, may stop writing
midway through a sector after power is
lost, leaving it mismatched against
its error-correcting code. The sector
is thus corrupt and its contents lost.
A physical journal guards against such
corruption because it holds a complete
copy of the sector, which it can
replay over the corruption upon next
mount.
Seems to suggest that some hard drives will not finish writing the sector, but that a journaling filesystem can protect you from data loss the same way the xlog protects a database.
From the linux kernel mailing list in a discussion on ext3 journaling filesystem:
In any case bad sector checksum is
hardware bug. Sector write is supposed
to be atomic, it either happens or
not.
I'd tend to believe that over the wiki comment. Actually, the very existence of a database (firebird) with no xlog implies that sector write is atomic, that it cannot clobber data you did not mean to change.
There's quite a bit of discussion Here about atomicity of sector writes, and again no agreement. But the people who are disagreeing seem to be talking about multiple-sector writes (which are not atomic on many modern hard-drives.) Those who are saying sector writes are atomic do seem to know more about what they're talking about.
The answer to your first question depends on the hardware involved. At least with some older hardware, the answer was yes -- a power failure could result it garbage being written to the disk. Most current disks, however, have a bit of a "UPS" built into the disk itself -- a capacitor that's large enough to power the disk long enough to write the data in the on-disk cache out to the disk platter. They also have circuitry to detect whether the power supply is still good, so when the power gets flaky, they write the data in the cache to the platter, and ignore garbage they might receive.
As far as a "torn page" goes, a typical disk only accepts commands to write an entire sector at a time, so what you'll get will normally be an integral number of sectors written correctly, and others remaining unchanged. If, however, you're using a logical page size that's larger than a single sector, you can certainly end up with a page that's partially written.
That, however, mostly applies to a direct connection to a normal moving-platter type hard drive. With almost anything else, the rules can and often will be different. Just for an obvious example, if you're writing over the network, you're mostly at the mercy of the network protocol in use. If you transmit data over TCP, data that doesn't match up with the CRC will be rejected, but the same data transmitted over UDP, with the same corruption, might be accepted.
I suspect this assumption is wrong.
Modern HDDs encode the data in sectors - and additionally protect it with ECC. Therefore you can end-up with garbaging all the sector content - it will just not make sense with the encoding used.
As for increasingly poplular SSDs, the situation is even more gruesome - the block is cleared prior to being overwritten, so, depending on the firmware being used and the amount of free space, entirely unrelated sectors can be damaged.
By the way, an OS crash will not lead to data being damaged within single sector.
I would expect one torn page to consist of part X, part Y, and part unreadable sector. If a head is in the middle of writing a sector when the power fails, the drive should park the heads immediately, so that the rest of the drive (aside from that one sector) will remain undamaged.
In some cases I would expect several torn pages consisting of part X and part Y, but only one torn page would include an unreadable sector. The reason for several torn pages is that the drive can buffer lots of writes internally, and the order of writing might interleave various sectors from various pages.
I've read conflicting stories about whether a new write to the unreadable sector will make it readable again. Even if the answer is yes, that will be new data Z, neither X nor Y.
when updating the
disk, the only guarantee drive manufactures make is that a single 512-
byte write is atomic (i.e., it will either complete in its entirety or it won’t
complete at all); thus, if an untimely power loss occurs, only a portion of
a larger write may complete (sometimes called a torn write).