Patent Application
20100328798
Referring to
Referring now to
The decrease in HDD throughput as a function of shake table vibration illustrated in
A system for determining vibration of at least one hard disk drive includes one or more computers configured to command a plurality of reads from the at least one hard disk drive such that, for each of the plurality of reads, data stored on the at least one hard disk drive is retrieved directly from the at least one hard disk drive. The one or more computers are also configured to obtain read rate information related to the plurality of reads and to determine a vibration level experienced by the at least one hard disk drive based on the read rate information.
A method for determining vibration of at least one hard disk drive includes commanding a plurality of writes to the at least one hard disk drive such that, for each of the plurality of writes, data is directly written to the at least one hard disk drive. The method also includes obtaining write rate information related to the plurality of writes and determining a vibration level experienced by the at least one hard disk drive based on the write rate information.
A computer-readable storage medium has information stored thereon for directing one or more computers to command a plurality of reads from at least one hard disk drive such that, for each of the plurality of reads, data stored on the at least one hard disk drive is retrieved directly from the at least one hard disk drive. The storage medium has further information stored thereon for directing the one or more computers to obtain read rate information related to the plurality of reads, and to determine a vibration level experienced by the at least one hard disk drive based on the read rate information.
While example embodiments in accordance with the invention are illustrated and disclosed, such disclosure should not be construed to limit the invention. It is anticipated that various modifications and alternative designs may be made without departing from the scope of the invention.
Vibration characterization is increasingly being performed with disk drives to assess and better understand their degradation mechanisms and to achieve improved vibrational health. It is common to externally instrument systems/drives with accelerometers and process the data to determine the amount of vibration the drives are experiencing. In certain circumstances, however, such instrumentation may be costly or impractical.
Vibration characterization may also be performed using HDD input and/or output (I/O) as a proxy for vibration levels. While these techniques may not require the use of accelerometers, caches throughout the system may mask the impact of vibration on the system during characterization.
As known in the art, a cache may be a temporary storage area where frequently accessed data can be stored for rapid access. Once the data is stored in the cache, it can be subsequently used by accessing the cached copy rather than re-fetching or re-computing the original data. Currently, there may be caches in the OS domain, caches in the network, caches inside the disk drives, etc. Caches are usually based on solid state flash technology, which has little to no sensitivity to vibration. Consequently, it is possible to get different inferred vibration metrics depending on, for example, whether a particular OS enables or disables a domain cache by default. Similarly, a vibration assessment script run on a system via remote login may yield completely different results compared with the same script run via a local console simply because of the presence/absence of a network cache.
Referring now to
Certain vibration characterization techniques described herein do not rely on accelerometers, and yet are relatively immune to the effects caches may have on I/O rates. In certain embodiments, a vibration-calibrated disk read/write activity generator that bypasses caches in the OS, network or HDD may be used in conjunction with system telemetry to infer vibration levels. Time and effort need not be spent on instrumenting the system with accelerometers. Additionally, more consistent and reproducible results may be obtained regardless of the presence/absence of flash-based caches in the system.
In one example, random reads are performed at the outer tracks of a disk drive with varying block sizes (e.g., block sizes increasing from 4 KB to 256 KB or greater). This may ensure that pre-fetching data from any read caches is not beneficial to performance by causing cache misses to occur. Hence, data is retrieved from the drive rather than the cache. Resulting read rates may be used to infer vibration level via, for example, a plot similar to that illustrated in
In another example, random (as opposed to sequential) writes are performed at the outer tracks of a disk drive using random data patterns. (Data from a file or a constant write pattern is not written.) Writes may be more sensitive to vibration than reads. This may ensure that caches are not involved in this process. Resulting write rates may be used to infer vibration level via, for example, a plot similar to that illustrated in
In yet another example, both reads and writes are performed on the disk raw device rather than the block (or logical) device to ensure that any OS buffers are not involved in this process. Resulting read and/or write rates may be used to infer vibration level as mentioned above.
The effect of vibration on I/O may be system/platform/drive type specific. I/O vibration signatures (similar to that illustrated in
To ensure that active caches do not mask the effects of vibration when characterizing systems based on read rates, the latency associated with reads of increasing block size may first be observed to determine a block size that necessarily bypasses any caches in the system as discussed below with reference to
Referring now to
Referring now to
At operation 20, the inference module 16 observes the latency associated with the reads based on information received from the telemetry tool 14.
At operation 22, the inference module 16 increments the block size by, for example, 4 KB.
At operation 24, the inference module 16 commands reads of the one or more HDDs 12 at the incremented block size, e.g., 16 KB.
At operation 26, the inference module observes the latency and I/O rates associated with the reads based on information received from the telemetry tool 14.
At operation 28, the inference module determines whether the latency associated with the reads commanded at operation 24 has substantially changed, e.g., doubled, etc., relative to the reads commanded previously. If yes, the inference module 16 determines the vibration level experienced by the one or more HDDs 12 based on the I/O rates using, for example, data similar to that illustrated in
The iterative process of incrementing read block size and observing corresponding latencies may be used to determine when caches within a system are being bypassed. If, for example, the latencies associated with read commands of block sizes between 4 KB and 128 KB remain relatively unchanged, one can assume that caches are in use. If the latencies associated with read commands of block sizes greater than 128 KB substantially change (relative to those of block sizes between 4 KB and 128 KB), one can assume that caches are no longer in use, and that data is being read directly from disk. Of course, if a particular block size is known (through testing or experience) to be of sufficient size such that caches are bypassed during reads, that block size, in certain embodiments, may be specified at the beginning of the process. Other scenarios are also possible.
Referring now to
At operation 34, the inference module 16 observes the I/O rates associated with the writes based on information received from the telemetry tool 14.
At operation 36, the inference module 16 determines the vibration level experienced by the one or more HDDs 12 based on the I/O rates using, for example, data similar to that illustrated in
Referring now to
As apparent to those of ordinary skill, the algorithms disclosed herein may be deliverable to a processing device in many forms including, but not limited to, (i) information permanently stored on non-writable storage media such as ROM devices and (ii) information alterably stored on writeable storage media such as floppy disks, magnetic tapes, CDs, RAM devices, and other magnetic and optical media. The algorithms may also be implemented in a software executable object. Alternatively, the algorithms may be embodied in whole or in part using suitable hardware components, such as Application Specific Integrated Circuits (ASICs), state machines, controllers or other hardware components or devices, or a combination of hardware, software and firmware components.
While embodiments of the invention have been illustrated and described, it is not intended that these embodiments illustrate and describe all possible forms of the invention. The words used in the specification are words of description rather than limitation, and it is understood that various changes may be made without departing from the spirit and scope of the invention.
