The present invention relates generally to a storage control system and more particularly to a system for data management.
Data storage, often called storage or memory, refers to computer components and recording media that retain digital data. Data storage is a core function and fundamental component of consumer and industrial electronics, especially devices such as computers, televisions, cellular phones, mobile devices, and digital video cameras.
Recently, forms of long-term storage other than electromechanical hard disks have become feasible for use in computers. NOT-AND (NAND) flash is one form of non-volatile memory used in solid-state storage devices. The memory cells are arranged in typical row and column fashion with circuitry for accessing individual cells. The memory transistors of those cells are placed to store an analog value that can be interpreted to hold two logical states in the case of Single Level Cell (SLC) or more than two logical states in the case of Multi Level Cell (MLC).
A flash memory cell is light in weight, occupies very little space, and consumes less power than electromechanical disk drives. Construction of a storage system with this type of memory allows for much higher bandwidths and input/output operations per second (IOPS) than typical electromechanical disk drives. More importantly, it is especially rugged and can operate at a much high temperature range. It will withstand without adverse effects repeated drops, each of which would destroy a typical electromechanical hard disk drive. A problem exhibited by flash memory is that it tends to have a limited life in use.
Thus, a need still remains for better data management devices. In view of the increasing demand for data management devices, it is increasingly critical that answers be found to these problems. In view of the ever-increasing commercial competitive pressures, along with growing consumer expectations and the diminishing opportunities for meaningful product differentiation in the marketplace, it is critical that answers be found for these problems. Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems.
Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.
The present invention provides a method of operation of a storage control system, including: receiving a recycle write from a recycle write queue; receiving a host write from a host write queue; and scheduling the recycle write and the host write for writing to a memory device.
The present invention provides a storage control system, including: a recycle write queue for providing a recycle write; a host write queue for providing a host write; and a scheduler, coupled to the recycle write queue and the host write queue, for scheduling the recycle write and the host write for writing to a memory device.
Certain embodiments of the invention have other steps or elements in addition to or in place of those mentioned above. The steps or elements will become apparent to those skilled in the art from a reading of the following detailed description when taken with reference to the accompanying drawings.
The following embodiments are described in sufficient detail to enable those skilled in the art to make and use the invention. It is to be understood that other embodiments would be evident based on the present disclosure, and that system, process, or mechanical changes may be made without departing from the scope of the present invention.
In the following description, numerous specific details are given to provide a thorough understanding of the invention. However, it will be apparent that the invention may be practiced without these specific details. In order to avoid obscuring the present invention, some well-known circuits, system configurations, and process steps are not disclosed in detail.
The drawings showing embodiments of the system are semi-diagrammatic and not to scale and, particularly, some of the dimensions are for the clarity of presentation and are shown exaggerated in the drawing FIGs.
Where multiple embodiments are disclosed and described having some features in common, for clarity and ease of illustration, description, and comprehension thereof, similar and like features one to another will ordinarily be described with similar reference numerals. The embodiments have been numbered first embodiment, second embodiment, etc. as a matter of descriptive convenience and are not intended to have any other significance or provide limitations for the present invention.
The term “module” referred to herein can include software, hardware, or a combination thereof in the present invention in accordance with the context in which the term is used. For example, the software can be machine code, firmware, embedded code, and application software. Also for example, the hardware can be circuitry, processor, computer, integrated circuit, integrated circuit cores, a microelectromechanical system (MEMS), passive devices, environmental sensors including temperature sensors, or a combination thereof.
Referring now to
The memory controller 104 provides data control and management of the memory array 106. The memory controller 104 interfaces with the host system 108 and controls the memory array 106 to transfer data between the host system 108 and the memory array 106.
The memory array 106 includes an array of memory devices 110 including flash memory devices or non-volatile memory devices. The memory array 106 can include pages of data or information. The host system 108 can request the memory controller 104 for reading, writing, and deleting data from or to a logical address space of a storage device or the memory sub-system 102 that includes the memory array 106.
Referring now to
The control unit 202 can be implemented in a number of different manners. For example, the control unit 202 can be a processor, an embedded processor, a microprocessor, a hardware control logic, a hardware finite state machine (FSM), a digital signal processor (DSP), or a combination thereof.
The control interface 210 can be used for communication between the control unit 202 and other functional units in the memory controller 104. The control interface 210 can also be used for communication that is external to the memory controller 104.
The control interface 210 can receive information from the other functional units or from external sources, or can transmit information to the other functional units or to external destinations. The external sources and the external destinations refer to sources and destinations external to the memory controller 104.
The control interface 210 can be implemented in different ways and can include different implementations depending on which functional units or external units are being interfaced with the control interface 210. For example, the control interface 210 can be implemented with a dedicated hardware including an application-specific integrated circuit (ASIC), a configurable hardware including a field-programmable gate array (FPGA), a discrete electronic hardware, or a combination thereof.
The storage unit 204 can include both hardware and the software 212. For example, the software 212 can include control firmware. The storage unit 204 can include a volatile memory, a nonvolatile memory, an internal memory, an external memory, or a combination thereof. For example, the storage unit 204 can be a nonvolatile storage such as non-volatile random access memory (NVRAM), Flash memory, disk storage, or a volatile storage such as static random access memory (SRAM).
The storage unit 204 can include a storage interface 214. The storage interface 214 can also be used for communication that is external to the memory controller 104. The storage interface 214 can receive information from the other functional units or from external sources, or can transmit information to the other functional units or to external destinations. The external sources and the external destinations refer to sources and destinations external to the memory controller 104.
The storage interface 214 can include different implementations depending on which functional units or external units are being interfaced with the storage unit 204. The storage interface 214 can be implemented with technologies and techniques similar to the implementation of the control interface 210.
The memory interface unit 206 can enable external communication to and from the memory controller 104. For example, the memory interface unit 206 can permit the memory controller 104 to communicate with the memory array 106 of
The memory interface unit 206 can include a memory interface 216. The memory interface 216 can be used for communication between the memory interface unit 206 and other functional units in the memory controller 104. The memory interface 216 can receive information from the other functional units or can transmit information to the other functional units.
The memory interface 216 can include different implementations depending on which functional units are being interfaced with the memory interface unit 206. The memory interface 216 can be implemented with technologies and techniques similar to the implementation of the control interface 210.
The host interface unit 208 allows the host system 108 of
The control unit 202 can operate the host interface unit 208 to send control or status information generated by the memory controller 104 to the host system 108. The control unit 202 can also execute the software 212 for the other functions of the memory controller 104. The control unit 202 can further execute the software 212 for interaction with the memory array 106 via the memory interface unit 206.
The functional units in the memory controller 104 can work individually and independently of the other functional units. For illustrative purposes, the memory controller 104 is described by operation of the memory controller 104 with the host system 108 and the memory array 106. It is understood that the memory controller 104, the host system 108, and the memory array 106 can operate any of the modules and functions of the memory controller 104.
Referring now to
Generally, the scheduler smoothing function 302 can include a host write queue 304, a recycle write queue 306, a scheduler 308, and a memory write operation queue 310. The memory write operation queue 310 can interleave host and recycle writes to the memory devices 110 of
Per the embodiments described herein, the term “host write” is defined herein as a physical write of new data from the host system 108 of
In general, the host write queue 304 can perform operations such as reads and writes submitted by a system external to the memory sub-system 102 of
During operation of the scheduler smoothing function 302, the host write queue 304 can send a host write request to the scheduler smoothing function 302. The host write request can be associated with a physical write of new data from the host system 108 to write to a particular logical address range. Per the embodiments described herein, the term “physical write” is defined herein as a write that goes to an end storage element of a system of memory, such as a volatile memory or a non-volatile memory including a NAND flash device.
During operation of the scheduler smoothing function 302, the recycle write queue 306 can also send a recycle write request to the scheduler smoothing function 302. The recycle write request can be associated with a physical write of data that the storage control system 100 is moving due to recycling. Per the embodiments described herein, the term “recycling” is defined herein as moving data from one page to another page, for purposes of either freeing up erase blocks to write new host data or to ensure that data on the erase blocks is preserved. Recycling can also be referred to as garbage collection.
Per the embodiments described herein, the term “erase block” is defined herein as a group of pages that is the smallest number of pages that can be erased at one time. Per the embodiments described herein, the term “page” is defined herein as the smallest group of data bytes that can be read from or written to in an erase block.
It is to be understood that write requests from the host write queue 304 and the recycle write queue 306 can include any type of write operation or request, such as competing writes, metadata writes, RAID/parity writes, etc.
After receiving a number of host write requests and/or recycle write requests, the scheduler smoothing function 302 can then determine which write operation or sequence of write operations to perform next to optimize performance of the storage control system 100. By way of example and not by way of limitation, the storage control system 100 can be optimized by providing a steady host performance to the user, a consistent host command latency period to the user, and/or maintenance of a desired recycle ratio.
Per the embodiments described herein, the term “recycle ratio” is defined herein as a number of logical pages that are written for recycling compared to a total number of data writes. Per the embodiments described herein, the term “host performance” is defined herein generally as how much work the host system 108 achieves when interfacing to the memory controller 104 including the SSD. For example, key measurements for the host performance can include throughput, average latency, worst-case latency, and latency deviation. The key measurements can be applied to any combinations of host write and host read distributions, sizes, and queue depths.
Once the scheduler smoothing function 302 has determined the correct write operation or sequence of write operations to perform next, the scheduler smoothing function 302 can then send this instruction to the memory write operation queue 310 for implementation within the memory array 106 of
Functions or operations of the memory controller 104 as described above can be implemented in hardware, software, or a combination thereof. The memory controller 104 can be implemented with the control unit 202 of
For example, the host write queue 304 can be implemented with the control unit 202 and the storage unit 204 to store and provide the host writes 314. Also for example, the recycle write queue 306 can be implemented with the control unit 202 and the storage unit 204 to store and provide the recycle writes 312.
For example, the scheduler 308 can be implemented with the control unit 202 to receive inputs from one or both of the host write queue 304 and the recycle write queue 306 to create an output write sequence that is delivered and implemented by the memory write operation queue 310. Also for example, the memory write operation queue 310 can be implemented with the control unit 202 and the storage unit 204 to receive sequence of write operations to perform next from the scheduler 308.
The host write queue 304 and the recycle write queue 306 can be coupled to the scheduler 308. The scheduler 308 can be coupled to the memory write operation queue 310.
The storage control system 100 is described with module functions or order as an example. The modules can be partitioned differently. For example, the scheduler 308 and the memory write operation queue 310 can be combined. Each of the modules can operate individually and independently of the other modules.
Furthermore, data generated in one module can be used by another module without being directly coupled to each other. The host write queue 304, the recycle write queue 306, the scheduler 308, and the memory write operation queue 310 can be implemented as hardware accelerators (not shown) within the control unit 202 or can be implemented as hardware accelerators (not shown) in the memory controller 104 or outside of the memory controller 104.
Referring now to
Generally, the memory devices 110 of
Generally, a correlation can exist between a write amplification 404 (WA) and the recycle ratio 402 required for a particular value of the write amplification 404. This correlation can be expressed as:
The recycle ratio 402 can be expressed as a function of the write amplification 404. Particularly, the recycle ratio 402 can be expressed as one minus a reciprocal of the write amplification 404.
Accordingly, even though the embodiments described herein generally focus on the recycle ratio 402, the principles can apply equally well to a method and/or system that utilizes the write amplification 404 measurements. Per the embodiments described herein, the term “write amplification” is defined herein as a ratio of physical writes to a media compared to the host writes 314 to the memory device 110.
In at least one embodiment, the scheduler smoothing function 302 can target a desired value of the recycle ratio 402. For example, if the scheduler smoothing function 302 knows a ratio of the host writes 314 that it should perform relative to total writes, it can target that ratio in its scheduling and as a result be as responsive to the host system 108 of
Accordingly, after receiving inputs from the host write queue 304 and the recycle write queue 306, the scheduler smoothing function 302 can then organize these inputs pursuant to a predefined value of a target recycle ratio 406. Per the embodiments described herein, the term “target recycle ratio” is defined herein as a recycle ratio that a scheduling algorithm is targeting. This is abbreviated as RRt.
For example, if the target recycle ratio 406 is 0.75, the scheduler smoothing function 302 can then output an instruction to the memory write operation queue 310 indicating that roughly three (3) of every four (4) writes should be the recycle writes 312. The target recycle ratio 406 of 0.75 is depicted in the memory write operation queue 310, wherein the order in which the scheduler smoothing function 302 can dispatch the write operations to the memory devices 110 is shown. However, it is to be understood that the target recycle ratio 406 is not limited to the preceding exemplary value of 0.75 and the target recycle ratio 406 can include any value between and including 0.0 and 1.0.
As such, when the behavior of the host system 108 varies and/or as the needs of the memory devices 110 change, the target recycle ratio 406 can change as well. Accordingly, in at least one embodiment of the invention, if the storage control system 100 of
It has been discovered that the scheduler smoothing function 302 permits enhanced flexibility for the needs of the host system 108 and the memory devices 110. For example, the scheduler smoothing function 302 permits the storage control system 100 to perform the recycle writes 312 when there is none of the host writes 314 to schedule. As such, this enhanced flexibility allows the memory devices 110 to catch up or get ahead on the recycle writes 312 so that it does not have to perform as many later on if the host system 108 decides to perform more of the host writes 314.
It has been discovered that the enhanced flexibility of the scheduler smoothing function 302 also permits the memory devices 110 to perform a burst of the host writes 314 even if the recycle ratio 402 would normally indicate doing more of the recycle writes 312. The scheduler smoothing function 302 of the present embodiments permits a burst of the host writes 314 because the memory devices 110 can perform additional recycle writes later thereby providing better performance to the host system 108 in cases where the host write activity is burst oriented.
Referring now to
Generally, the storage control system 100, when under a constant host workload, can dynamically determine a steady-state recycle ratio or the recycle ratio 402 from the first exemplary graph. In at least one embodiment, the steady state recycle ratio or value can be determined by having the storage control system 100 sample an available spare pool size or the spare pool size 502 and assigning a corresponding recycle ratio or the recycle ratio 402. As such, the recycle ratio 402 can be set based on a current size of a spare pool or the spare pool size 502.
Accordingly, in at least one embodiment, as the spare pool shrinks in size, the storage control system 100 can increase the recycle ratio 402. Conversely, as the spare pool increases in size, the memory system can decrease the recycle ratio 402. One possible correlation between the spare pool size 502 and the recycle ratio 402 is depicted in
Generally, the first exemplary graph includes a first region 504 and a second region 506. The first region 504 can include a substantially horizontal portion of the graph wherein the value of the recycle ratio 402 remains substantially constant around a value of one (1) over a range of the spare pool size 502 that varies from zero (0) erase blocks left to a value deemed “critically low.” The numerical value assigned to the qualitative term “critically low” can be predetermined or it can be empirically determined.
In at least one embodiment, factors used to empirically determine the value can include, but are not limited to, age of the memory devices 110 of
The second region 506 can include a substantially linear portion of the graph with a decreasing slope, wherein the value of the recycle ratio 402 decreases from around a value of one (1) to a value of zero (0). The value of the recycle ratio 402 can decrease over a range of the spare pool size 502 that varies from a value deemed “critically low” to a value corresponding to the “maximum” spare pool size. The numerical value assigned to the qualitative term “maximum” can be predetermined or it can be empirically determined.
In at least one embodiment, if the spare pool grows to a maximum size, the memory devices 110 can stop performing recycle operations because the recycle ratio 402 can be set to zero. However, it will be appreciated by those skilled in the art that the memory devices 110 need not totally stop performing recycle operations and can continue performing background-recycling operations. Generally, the value of the spare pool size 502 between “critically low” and “maximum” can act as a buffer region to help determine the potentially optimal steady state value for the recycle ratio 402.
It will be appreciated by those skilled in the art that if the recycle ratio 402 is not high enough to maintain a steady state for the storage control system 100, the size of the spare pool or the spare pool size 502 can decrease. Accordingly, in response, the first exemplary graph of the present embodiments would adjust the recycle ratio 402 to a higher value. In such cases, one of two things can happen: 1) the recycle ratio 402 can be set to a high enough value to be sustainable, or 2) the spare pool can become “critically low” and servicing of host operations can cease.
If the recycle ratio 402 is set to a high enough value to be sustainable, the storage control system 100 should reach a steady state in regards to a number of recycle operations that are performed for every host operation. It will be appreciated by those skilled in the art that when in this steady state, the spare pool size 502 changes very little, if at all.
If the spare pool becomes critically low and servicing of host operations ceases, the first exemplary graph can command the storage control system 100 to perform only recycle operations. In such cases, once the spare pool size 502 gets above this critically low mark, the recycle ratio 402 can be set to a value that allows some host operations to be serviced. It will be appreciated by those skilled in the art that this critically low mark should be used only in extreme cases as a safety net to prevent device failure or extended inoperable responses.
Once a steady state for a particular host workload is determined, the recycle ratio 402 and the host performance should be constant. However, when the host changes the workload, a different steady state can be required by the storage control system 100. For example, if the new workload requires a higher value of the recycle ratio 402, the spare pool can shrink and the storage control system 100 can adapt by increasing the recycle ratio 402 until it reaches a new steady state.
Conversely, if the new workload requires a lower value of the recycle ratio 402, the spare pool can slowly grow. It will be appreciated by those skilled in the art that in response to the larger spare pool, the recycle ratio 402 can decrease pursuant to the first exemplary graph thereby permitting more of the host writes 314 of
As such, a method and/or system have been discovered for dynamically adjusting the recycle ratio 402 of the memory devices 110. The dynamic adjustment of the recycle ratio 402 of the present embodiments happens directly because of the spare pool shrinking or growing in size, so the memory devices 110 do not have to try to predict the recycle ratio 402 that can be needed by the host system 108 of
It will be appreciated by those skilled in the art that additional equations and/or curves can be used to translate the spare pool size 502 into a target value of the recycle ratio 402. Accordingly, the function or algorithm used to determine the recycle ratio 402 does not have to be linear in regards to the spare pool size 502. The function may be exponential, logarithmic, mapping, etc.
It will be appreciated by those skilled in the art that if the recycle ratio 402 reaches a value of one (1) (e.g., the maximum value), the scheduler smoothing function 302 need not service the host writes 314.
It will also be appreciated by those skilled in the art that the current embodiments permit the memory devices 110 to perform some recycling operations including the recycle writes 312 of
Referring now to
The second exemplary graph can include a transition region 602 and a stable region 604. The transition region 602 includes a portion of the graph wherein the recycle ratio 402 experiences a relatively large change over a relatively small range of the spare pool size 502. In at least one embodiment, the recycle ratio 402 can change by five percent (5%) or more in the transition region 602.
The stable region 604 marks a portion of the second exemplary graph wherein the recycle ratio 402 remains relatively constant over a range of values of the spare pool size 502. By way of example and not by way of limitation, the spare pool size 502 can change by five percent (5%) or more in the stable region 604, while the recycle ratio 402 can remain relatively constant over that range. As such, the second exemplary graph permits a correlation between the recycle ratio 402 and the spare pool size 502 that can adjust in ranges.
It will be appreciated by those skilled in the art that additional equations and/or curves can be used to translate the spare pool size 502 into the target value of the recycle ratio 402. Accordingly, the function or algorithm used to determine the recycle ratio 402 does not have to be linear in regards to the spare pool size 502. The function can be exponential, logarithmic, mapping, etc.
Referring now to
Generally, when the host system 108 of
A dotted line depicts a transitional period response of the transitional period 704 for the embodiments described herein, wherein host performance degradation is minimized. It will be appreciated by those skilled in the art that host performance degradation is minimized with the transitional period response of the dotted line because the change in the recycle ratio 402 is minimized. A dashed line above the dotted line depicts another transitional period response of the transitional period 704 wherein the host experiences greater host performance degradation due to the larger increase in the recycle ratio 402.
It has been discovered that by using the recycle ratio 402 functions described herein and/or the spare pool size 502 of
Referring now to
In at least one embodiment, the scheduler smoothing function 302 can implement the recycle ratio 402 of
The smoothing feedback loop can begin with an update RRc module 803. The update RRc module 803 ensures that the smoothing feedback loop utilizes the most current recycle ratio or the most current value of the recycle ratio 402 for its algorithm or calculation. In at least one embodiment, the update RRc module 803 can determine the current recycle ratio 802 or a current value of the recycle ratio 402 by utilizing inputs from a schedule host write module 812 and/or a schedule recycle write module 816. The current value of the recycle ratio 402 of the update RRc module 803 can then be fed to a comparison module 804.
In the comparison module 804, the current recycle ratio 802 can be compared to the target recycle ratio 406 (RR). Generally, if the current recycle ratio 802 is greater than or equal to the target recycle ratio 406, the smoothing feedback loop can choose a first path. If the current recycle ratio 802 is less than the target recycle ratio 406, the smoothing feedback loop can choose a second path.
Accordingly, in at least one embodiment, if the current recycle ratio 802 is greater than or equal to the target recycle ratio 406 (RRc≥RRt), the smoothing feedback loop can then move to a host scheduler module 808. Upon receiving an input from the comparison module 804, the host scheduler module 808 can determine if there is one of the host writes 314 to schedule. If there is one of the host writes 314 to schedule, the smoothing feedback loop can then move to the schedule host write module 812. The schedule host write module 812 can then send its schedule host write request to the update RRc module 803 to be used in determining the current recycle ratio 802.
If there is none of the host writes 314 to schedule at the host scheduler module 808, the smoothing feedback loop can then move to a recycle scheduler module 810. If there is one of the recycle writes 312 to schedule, the smoothing feedback loop can then move to the schedule recycle write module 816. The schedule recycle write module 816 can then send its schedule recycle write request to the update RRc module 803 to be used in determining the current recycle ratio 802. If there is none of the recycle writes 312 to schedule when the smoothing feedback loop reaches the recycle scheduler module 810, the smoothing feedback loop can then move back to the comparison module 804.
In another embodiment, if the current recycle ratio 802 is less than the target recycle ratio 406 (RRc<RRt) or there is none of the recycle writes 312 to schedule from the recycle scheduler module 810 when the smoothing feedback loop reaches the comparison module 804, the smoothing feedback loop can then move to a host write burst module 814. If the smoothing feedback loop determines that a host write burst can be performed at the host write burst module 814, the smoothing feedback loop can then move to the host scheduler module 808 and can proceed as described above. If the smoothing feedback loop determines that a host write burst cannot be performed at the host write burst module 814, the smoothing feedback loop can then move to the recycle scheduler module 810 and can proceed as described above.
It will be appreciated by those skilled in the art that the smoothing feedback loop optimizes host performance by keeping the current recycle ratio 802 close to the target recycle ratio 406 when a steady stream of host activity is observed. By way of example and not by way of limitation, when the steady stream of the host activity is observed, the current recycle ratio 802 is kept within plus or minus ten percent (10%) of the target recycle ratio 406.
It will be appreciated by those skilled in the art that the smoothing feedback loop optimizes host performance by allowing the current recycle ratio 802 to drop relative to the target recycle ratio 406 for a short period of time when a burst of the host activity is observed. By way of example and not by way of limitation, the current recycle ratio 802 varies by about ten percent (10%) from the target recycle ratio 406 in such instances.
It will be appreciated by those skilled in the art that the smoothing feedback loop optimizes host performance by allowing the current recycle ratio 802 to grow or increase relative to the target recycle ratio 406 for a period of time when a lull in host activity is observed. By way of example and not by way of limitation, the current recycle ratio 802 varies by about ten percent (10%) from the target recycle ratio 406 in such instances.
It has been discovered that such a method and/or system enhances the flexibility of the memory devices 110 of
Functions or operations of the memory controller 104 as described above can be implemented in hardware, software, or a combination thereof. The memory controller 104 can be implemented with the control unit 202 of
For example, the update RRc module 803 can be implemented with the control unit 202 to ensure that the smoothing feedback loop utilizes the most current value of the recycle ratio 402 and determine the current value of the recycle ratio 402 by utilizing inputs from the schedule host write module 812 and/or the schedule recycle write module 816. Also for example, the comparison module 804 can be implemented with the control unit 202 to compare the current recycle ratio 802 to the target recycle ratio 406.
For example, the host scheduler module 808 can be implemented with the control unit 202 to determine if there is one of the host writes 314 to schedule. Also for example, the recycle scheduler module 810 can be implemented with the control unit 202 to determine if there is one of the recycle writes 312 to schedule.
For example, the schedule host write module 812 can be implemented with the control unit 202 to schedule the host writes 314. Also for example, the host write burst module 814 can be implemented with the control unit 202 to determine if a host write burst can be performed. Further, for example, the schedule recycle write module 816 can be implemented with the control unit 202 to schedule one of the recycle writes 312.
The update RRc module 803 can be coupled to the comparison module 804, the schedule host write module 812, and the schedule recycle write module 816. The comparison module 804 can be coupled to the host scheduler module 808, the recycle scheduler module 810, and the host write burst module 814.
The host scheduler module 808 can be coupled to the recycle scheduler module 810, the schedule host write module 812, and the host write burst module 814. The recycle scheduler module 810 can be coupled to the host write burst module 814 and the schedule recycle write module 816.
The storage control system 100 of
Furthermore, data generated in one module can be used by another module without being directly coupled to each other. The update RRc module 803, the comparison module 804, and the host scheduler module 808 can be implemented as hardware accelerators (not shown) within the control unit 202 or can be implemented as hardware accelerators (not shown) in the memory controller 104 or outside of the memory controller 104. The recycle scheduler module 810, the schedule host write module 812, the host write burst module 814, and the schedule recycle write module 816 can be implemented as hardware accelerators (not shown) within the control unit 202 or can be implemented as hardware accelerators (not shown) in the memory controller 104 or outside of the memory controller 104.
Referring now to
In at least one embodiment, a moving average of recent writes can be used to adjust the current recycle ratio 802. In such cases, the moving average of the recent writes can be sampled from a flash write operation queue or the memory write operation queue 310.
The memory write operation queue 310 can include one or more write commands, including the host writes 314 and/or the recycle writes 312. The host writes 314 and the recycle writes 312 within the memory write operation queue 310 can be recent write operations.
The recent write operations can be given weighting factors or weights 908 using multiplication modules 910. Based on the weights 908, the moving average smoothing function 902 can determine whether the host writes 314 or the recycle writes 312 should happen next. The moving average smoothing function 902 can also feed the decision into a recent history window so that it can influence the next decision. Outputs of the multiplication modules 910 can be fed to a summation module 912 to calculate the current recycle ratio 802.
Functions or operations of the memory controller 104 of
For example, the multiplication modules 910 can be implemented with the control unit 202 to multiply the recent write operations, including the recycle writes 312 and the host writes 314, and the weights 908. Also for example, the summation module 912 can be implemented with the control unit 202 to calculate the current recycle ratio 802 based on the outputs or results of the multiplication modules 910. The multiplication modules 910 can be coupled to the summation module 912 and the memory write operation queue 310.
The storage control system 100 of
Furthermore, data generated in one module can be used by another module without being directly coupled to each other. The multiplication modules 910 and the summation module 912 can be implemented as hardware accelerators (not shown) within the control unit 202 or can be implemented as hardware accelerators (not shown) in the memory controller 104 or outside of the memory controller 104.
Referring now to
A preferred method of tracking the current recycle ratio 802 using a moving average can include an exponential moving average because it can be the easiest to compute. The exponential moving average can be the easiest to compute because it can require only the current recycle ratio 802, denoted as RRC(n), not a buffer of previous decisions.
The exponential moving average can require no divisions, but instead, just or only a subtraction module 1004, a multiplication module 1006, and an addition module 1008 each time. In addition, the exponential moving average can behave well on fixed-point hardware. If all writes for a chosen window size are given equal weights, the smoothing function can be a simple-moving average function that is similar to a batch smoothing function, which will be subsequently described.
The functional block diagram depicts a decision module 1010, which determines a decision, denoted as Δ(n), of whether the host writes 314 of
A subtraction result from the subtraction module 1004 can be multiplied by an exponential average parameter or a weight 1012, denoted as α, by the multiplication module 1006, a result of which can then be added to the current recycle ratio 802 by the addition module 1008 to generate an updated current recycle ratio 1014, denoted as RRC(N+1). The updated current recycle ratio 1014 can be fed to a unit delay module 1016 to delay the updated current recycle ratio 1014 by a predetermined unit of time to generate a value of the current recycle ratio 802 for subsequent processing.
The functional block diagram depicts an initialization module 1018. The initialization module 1018 configures the current recycle ratio 802 (RRc) for the scheduler smoothing function 302. For example, a good starting point is to set the current recycle ratio 802 to be equal to the target recycle ratio 406 (RRt) of
In the drive, the target recycle ratio 406 can be calculated every time the spare pool size 502 of
Functions or operations of the memory controller 104 of
For example, the subtraction module 1004 can be implemented with the control unit 202 to subtract the current recycle ratio 802 from the decision of whether the host writes 314 or the recycle writes 312 should happen next. Also for example, the multiplication module 1006 can be implemented with the control unit 202 to multiply the subtraction result from the subtraction module 1004 by the weight 1012.
For example, the addition module 1008 can be implemented with the control unit 202 to add the result of the multiplication module 1006 to the current recycle ratio 802 to generate the updated current recycle ratio 1014. Also for example, the decision module 1010 can be implemented with the control unit 202 to determine the decision of whether the host writes 314 or the recycle writes 312 should happen next.
For example, the unit delay module 1016 can be implemented with the control unit 202 to delay the updated current recycle ratio 1014 by the predetermined unit of time to generate the value of the current recycle ratio 802. Also for example, the initialization module 1018 can be implemented with the control unit 202 to generate and supply initialization parameters for the target recycle ratio 406 of
The subtraction module 1004 can be coupled to the multiplication module 1006, the decision module 1010, and the initialization module 1018. The decision module 1010 can be coupled to the addition module 1008. The addition module 1008 can be coupled to the unit delay module 1016 and the initialization module 1018.
The storage control system 100 of
Furthermore, data generated in one module can be used by another module without being directly coupled to each other. The subtraction module 1004, the multiplication module 1006, the addition module 1008, the decision module 1010, the unit delay module 1016, and the initialization module 1018 can be implemented as hardware accelerators (not shown) within the control unit 202 or can be implemented as hardware accelerators (not shown) in the memory controller 104 or outside of the memory controller 104.
Referring now to
This type of smoothing function considers work in batches, using the target recycle ratio 406 of
For example,
The scheduler 308 can then work its way down the scheduler 308, pulling from an appropriate write queue for a host slot 1106 or a recycle slot 1108, for which the scheduler 308 is currently processes. The appropriate write queue can be the host write queue 304 or the recycle write queue 306. The scheduler 308 can pull the host writes 314 or the recycle writes 312 from the appropriate write queue for the host slot 1106 or the recycle slot 1108, respectively.
The scheduler 308 can update the memory write operation queue 310 with an order by which the host writes 314 and the recycle writes 312 are executed. When a batch completes, the scheduler 308 can create a new schedule or another of the schedule 1104, if necessary.
With the batch smoothing function 1102, the scheduler 308 can still choose to deviate from the target recycle ratio 406 for periods of time, as indicated in
It has been discovered that the memory sub-system 102 of
It has also been discovered that the memory sub-system 102 including the SSD with the scheduler smoothing function 302 that utilizes the target recycle ratio 406 improves host performance. The host performance is improved by using the target recycle ratio 406 to schedule the mixture of the host writes 314 and the recycle writes 312 to maintain steady host performance and consistent host command latencies.
It has further been discovered that the memory sub-system 102 including the SSD with the scheduler smoothing function 302 that utilizes a target write amplification to schedule a mixture of the host writes 314 and the recycle writes 312 improves host performance by providing steady host performance and consistent host command latencies.
It has further been discovered that the memory sub-system 102 dynamically determining the recycle ratio 402 of
It has further been discovered that the memory sub-system 102 adjusting the recycle ratio 402 based on the spare pool size 502 of
It has further been discovered that the scheduler smoothing function 302 ceases servicing the host writes 314 only if the recycle ratio 402 reaches one (1) or the spare pool size 502 becomes critically low provides improved reliability by servicing only the recycle writes 312 to increase the spare pool size 502 to prevent device failure or extended inoperable responses.
It has further been discovered that the memory sub-system 102 including the SSD stops or ceases to perform recycle operations or the recycle writes 312 altogether if the recycle ratio 402 becomes zero improves host performance by servicing only the host writes 314 in response to the larger spare pool.
It has further been discovered that the memory sub-system 102 including the SSD continues to perform the recycling operations in the background at a low rate if the recycle ratio 402 becomes zero improves host performance by servicing more of the host writes 314 in response to the larger spare pool.
It has further been discovered that the memory sub-system 102 optimizes host performance by adjusting the recycle ratio 402 and the spare pool size 502 to help even out host performance during workload transitions or the transitional period 704 of
It has further been discovered that the memory sub-system 102 including the SSD performing some of the recycle writes 312 when there are no host operations or the host writes 314 provides improved reliability. The improved reliability is provided because the recycle writes 312 increase the spare pool size 502 thereby preventing device failure or extended inoperable responses.
It has further been discovered that a solid-state drive (SSD) or the memory sub-system 102 that updates the target recycle ratio 406 based on host and drive activity to update the scheduler smoothing function 302 improves host performance by maintaining steady host performance and consistent host command latencies. The target recycle ratio 406 is updated based on the host and drive activity based on an appropriate mixture of the host writes 314 and the recycle writes 312.
It has further been discovered that the SSD or the memory sub-system 102 with the scheduler smoothing function 302 that employs the smoothing feedback loop improves host performance by maintaining steady host performance and consistent host command latencies. The host performance is improved using the smoothing feedback loop to converge on the target recycle ratio 406.
It has further been discovered that the SSD or the memory sub-system 102 with the scheduler smoothing function 302 that schedules a mixture by utilizing the moving average smoothing function 902 of
It has further been discovered that the SSD or the memory sub-system 102 with the scheduler smoothing function 302 that allows the SSD to get ahead on its maintenance/recycling work improves host performance by maintaining steady host performance and consistent host command latencies. The SSD gets ahead on its maintenance/recycling work by scheduling extra cycles for the recycle writes 312 when the host system 108 is not sending full of the host writes 314.
It has further been discovered that the SSD or the memory sub-system 102 with the scheduler smoothing function 302 that allows the SSD to service a burst of the host writes 314 improves host performance by maintaining steady host performance and consistent host command latencies. The host performance is improved by the comparison module 804 of
It has further been discovered that the SSD or the memory sub-system 102 with the scheduler smoothing function 302 that schedules a mixture of the host writes 314 and the recycle writes 312 improves host performance by maintaining steady host performance and consistent host command latencies. The host performance is improved by choosing which types of writes to schedule, including the host writes 314 and the recycle writes 312, in batches using the batch smoothing function 1102 in accordance with the target recycle ratio 406.
The physical transformation of scheduling the recycle writes 312 and the host writes 314 based on the recycle ratio 402 for writing to the memory devices 110 of
Referring now to
Thus, it has been discovered that the storage control system of the present invention furnishes important and heretofore unknown and unavailable solutions, capabilities, and functional aspects for a storage control system with data management mechanism. The resulting method, process, apparatus, device, product, and/or system is straightforward, cost-effective, uncomplicated, highly versatile, accurate, sensitive, and effective, and can be implemented by adapting known components for ready, efficient, and economical manufacturing, application, and utilization.
Another important aspect of the present invention is that it valuably supports and services the historical trend of reducing costs, simplifying systems, and increasing performance.
These and other valuable aspects of the present invention consequently further the state of the technology to at least the next level.
While the invention has been described in conjunction with a specific best mode, it is to be understood that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the aforegoing description. Accordingly, it is intended to embrace all such alternatives, modifications, and variations that fall within the scope of the included claims. All matters hithertofore set forth herein or shown in the accompanying drawings are to be interpreted in an illustrative and non-limiting sense.
Number | Name | Date | Kind |
---|---|---|---|
4048481 | Bailey, Jr. et al. | Sep 1977 | A |
4839587 | Flatley et al. | Jun 1989 | A |
5034744 | Obinata | Jul 1991 | A |
5210854 | Beaverton et al. | May 1993 | A |
5311395 | McGaha et al. | May 1994 | A |
5450354 | Sawada et al. | Sep 1995 | A |
5479638 | Assar et al. | Dec 1995 | A |
5784174 | Fujino et al. | Jul 1998 | A |
5790828 | Jost | Aug 1998 | A |
5930504 | Gabel | Jul 1999 | A |
5949785 | Beasley | Sep 1999 | A |
5963893 | Sakakura et al. | Oct 1999 | A |
6034897 | Estakhri et al. | Mar 2000 | A |
6069827 | Sinclair | May 2000 | A |
6091652 | Haehn et al. | Jul 2000 | A |
6275436 | Tobita et al. | Aug 2001 | B1 |
6345367 | Sinclair | Feb 2002 | B1 |
6356447 | Scafidi | Mar 2002 | B2 |
6381176 | Kim et al. | Apr 2002 | B1 |
6381670 | Lee et al. | Apr 2002 | B1 |
6412080 | Fleming et al. | Jun 2002 | B1 |
6529997 | Debiez et al. | Mar 2003 | B1 |
6552581 | Gabara | Apr 2003 | B1 |
6587915 | Kim | Jul 2003 | B1 |
6618249 | Fairchild | Sep 2003 | B2 |
6661503 | Yamaguchi et al. | Dec 2003 | B1 |
6728913 | Parker | Apr 2004 | B1 |
6763424 | Conley | Jul 2004 | B2 |
6775792 | Ulrich et al. | Aug 2004 | B2 |
6778387 | Fairchild | Aug 2004 | B2 |
6850443 | Lofgren et al. | Feb 2005 | B2 |
6854070 | Johnson et al. | Feb 2005 | B2 |
6871304 | Hadjihassan et al. | Mar 2005 | B2 |
6903972 | Lasser et al. | Jun 2005 | B2 |
6906961 | Eggleston et al. | Jun 2005 | B2 |
6975028 | Wayburn et al. | Dec 2005 | B1 |
7082495 | DeWhitt et al. | Jul 2006 | B2 |
7107389 | Inagaki et al. | Sep 2006 | B2 |
7139864 | Bennett et al. | Nov 2006 | B2 |
7233497 | Simon et al. | Jun 2007 | B2 |
7243186 | Liang et al. | Jul 2007 | B2 |
7298888 | Hamar | Nov 2007 | B2 |
7330927 | Reeve et al. | Feb 2008 | B1 |
7333364 | Yu et al. | Feb 2008 | B2 |
7350101 | Nguyen et al. | Mar 2008 | B1 |
7355896 | Li et al. | Apr 2008 | B2 |
7434122 | Jo | Oct 2008 | B2 |
7441067 | Gorobets et al. | Oct 2008 | B2 |
7516267 | Coulson et al. | Apr 2009 | B2 |
7558109 | Brandman et al. | Jul 2009 | B2 |
7613871 | Tanaka et al. | Nov 2009 | B2 |
7620710 | Kottomtharayil et al. | Nov 2009 | B2 |
7620769 | Lee et al. | Nov 2009 | B2 |
7639532 | Roohparvar et al. | Dec 2009 | B2 |
7661054 | Huffman et al. | Feb 2010 | B2 |
7679948 | Park et al. | Mar 2010 | B2 |
7693422 | Alicherry et al. | Apr 2010 | B2 |
7738502 | Chang et al. | Jun 2010 | B2 |
7743216 | Lubbers et al. | Jun 2010 | B2 |
7818525 | Frost et al. | Oct 2010 | B1 |
7827348 | Lee et al. | Nov 2010 | B2 |
7830164 | Earle et al. | Nov 2010 | B2 |
7853749 | Kolokowsky | Dec 2010 | B2 |
7979614 | Yang | Jul 2011 | B1 |
8000161 | Stan et al. | Aug 2011 | B2 |
8001135 | Perlmutter et al. | Aug 2011 | B2 |
8010738 | Chilton et al. | Aug 2011 | B1 |
8028123 | Kilzer et al. | Sep 2011 | B2 |
8046645 | Hsu et al. | Oct 2011 | B2 |
8051241 | Feldman et al. | Nov 2011 | B2 |
8072805 | Chou et al. | Dec 2011 | B2 |
8095724 | Ji et al. | Jan 2012 | B2 |
8095765 | Asnaashari et al. | Jan 2012 | B2 |
8117396 | Fair et al. | Feb 2012 | B1 |
8127202 | Cornwell et al. | Feb 2012 | B2 |
8145984 | Sommer et al. | Mar 2012 | B2 |
8154921 | Mokhlesi et al. | Apr 2012 | B2 |
8169825 | Shalvi et al. | May 2012 | B1 |
8205028 | Sakarda | Jun 2012 | B1 |
8209677 | Shintani et al. | Jun 2012 | B2 |
8219724 | Caruso et al. | Jul 2012 | B1 |
8219776 | Forhan et al. | Jul 2012 | B2 |
8228701 | Sokolov et al. | Jul 2012 | B2 |
8245101 | Olbrich et al. | Aug 2012 | B2 |
8250621 | Cha | Aug 2012 | B2 |
8254172 | Kan | Aug 2012 | B1 |
8259506 | Sommer et al. | Sep 2012 | B1 |
8289801 | Smith et al. | Oct 2012 | B2 |
8296534 | Gupta et al. | Oct 2012 | B1 |
8332578 | Frickey, III et al. | Dec 2012 | B2 |
8363413 | Paquette et al. | Jan 2013 | B2 |
8369141 | Sommer et al. | Feb 2013 | B2 |
8385860 | Tseng et al. | Feb 2013 | B2 |
8386700 | Olbrich et al. | Feb 2013 | B2 |
8397101 | Goss et al. | Mar 2013 | B2 |
8407409 | Kawaguchi | Mar 2013 | B2 |
8464106 | Filor et al. | Jun 2013 | B2 |
8503238 | Wu et al. | Aug 2013 | B1 |
8521981 | Strauss et al. | Aug 2013 | B2 |
8560770 | Haines et al. | Oct 2013 | B2 |
8601203 | Holbrook et al. | Dec 2013 | B2 |
8612669 | Syu et al. | Dec 2013 | B1 |
8612804 | Kang et al. | Dec 2013 | B1 |
8661184 | Wood et al. | Feb 2014 | B2 |
8694811 | Raju et al. | Apr 2014 | B2 |
8725931 | Kang | May 2014 | B1 |
8750052 | Aoki et al. | Jun 2014 | B2 |
8793556 | Northcott et al. | Jul 2014 | B1 |
8799747 | Goss et al. | Aug 2014 | B2 |
8832506 | Griffin et al. | Sep 2014 | B2 |
8862818 | Ozdemir | Oct 2014 | B1 |
8880838 | Kaiser et al. | Nov 2014 | B2 |
8984216 | Fillingim | Mar 2015 | B2 |
9043668 | Goss et al. | May 2015 | B2 |
9063844 | Higgins et al. | Jun 2015 | B2 |
9069468 | Mehra et al. | Jun 2015 | B2 |
9116401 | Kim et al. | Aug 2015 | B2 |
20020056025 | Qiu et al. | May 2002 | A1 |
20020156891 | Ulrich et al. | Oct 2002 | A1 |
20020159285 | Morley et al. | Oct 2002 | A1 |
20030033308 | Patel et al. | Feb 2003 | A1 |
20030046603 | Harari et al. | Mar 2003 | A1 |
20030074592 | Hasegawa | Apr 2003 | A1 |
20030163633 | Aasheim et al. | Aug 2003 | A1 |
20040080985 | Chang et al. | Apr 2004 | A1 |
20040088511 | Bacon et al. | May 2004 | A1 |
20040252670 | Rong et al. | Dec 2004 | A1 |
20050021904 | Iaculo et al. | Jan 2005 | A1 |
20050038792 | Johnson | Feb 2005 | A1 |
20050073884 | Gonzalez et al. | Apr 2005 | A1 |
20050076102 | Chen et al. | Apr 2005 | A1 |
20050144516 | Gonzalez et al. | Jun 2005 | A1 |
20060015683 | Ashmore et al. | Jan 2006 | A1 |
20060020745 | Conley et al. | Jan 2006 | A1 |
20060022054 | Elhamias et al. | Feb 2006 | A1 |
20060080505 | Arai et al. | Apr 2006 | A1 |
20060136682 | Haridas et al. | Jun 2006 | A1 |
20060143365 | Kikuchi | Jun 2006 | A1 |
20060143475 | Herbert et al. | Jun 2006 | A1 |
20060253641 | Gatzemeier et al. | Nov 2006 | A1 |
20060256624 | Eggleston et al. | Nov 2006 | A1 |
20060282644 | Wong | Dec 2006 | A1 |
20060294574 | Cha | Dec 2006 | A1 |
20070050536 | Kolokowsky | Mar 2007 | A1 |
20070061511 | Faber | Mar 2007 | A1 |
20070067598 | Fujimoto | Mar 2007 | A1 |
20070079152 | Winick et al. | Apr 2007 | A1 |
20070083779 | Misaka et al. | Apr 2007 | A1 |
20070226592 | Radke | Sep 2007 | A1 |
20070234004 | Oshima et al. | Oct 2007 | A1 |
20070260811 | Merry, Jr. et al. | Nov 2007 | A1 |
20070263444 | Gorobets et al. | Nov 2007 | A1 |
20070276973 | Tan et al. | Nov 2007 | A1 |
20080028246 | Witham | Jan 2008 | A1 |
20080046630 | Lasser | Feb 2008 | A1 |
20080052446 | Lasser et al. | Feb 2008 | A1 |
20080082736 | Chow et al. | Apr 2008 | A1 |
20080126720 | Danilak | May 2008 | A1 |
20080183918 | Dhokia et al. | Jul 2008 | A1 |
20080189588 | Tanaka et al. | Aug 2008 | A1 |
20080263289 | Hosoya et al. | Oct 2008 | A1 |
20080313505 | Lee et al. | Dec 2008 | A1 |
20090006900 | Lastras-Montano et al. | Jan 2009 | A1 |
20090019321 | Radke | Jan 2009 | A1 |
20090070651 | Diggs et al. | Mar 2009 | A1 |
20090083587 | Ng et al. | Mar 2009 | A1 |
20090089485 | Yeh | Apr 2009 | A1 |
20090091990 | Park et al. | Apr 2009 | A1 |
20090109786 | Ye et al. | Apr 2009 | A1 |
20090125670 | Keays | May 2009 | A1 |
20090132756 | Hsieh | May 2009 | A1 |
20090138654 | Sutardja | May 2009 | A1 |
20090146721 | Kurooka et al. | Jun 2009 | A1 |
20090157948 | Trichina et al. | Jun 2009 | A1 |
20090164702 | Kern | Jun 2009 | A1 |
20090164710 | Choi et al. | Jun 2009 | A1 |
20090172248 | You | Jul 2009 | A1 |
20090172262 | Olbrich et al. | Jul 2009 | A1 |
20090179707 | Higashino | Jul 2009 | A1 |
20090183183 | Muppirala et al. | Jul 2009 | A1 |
20090228634 | Nakamura et al. | Sep 2009 | A1 |
20090228761 | Perlmutter et al. | Sep 2009 | A1 |
20090259819 | Chen et al. | Oct 2009 | A1 |
20090259896 | Hsu et al. | Oct 2009 | A1 |
20090271562 | Sinclair | Oct 2009 | A1 |
20090287975 | Kim et al. | Nov 2009 | A1 |
20090300238 | Panabaker et al. | Dec 2009 | A1 |
20090323419 | Lee et al. | Dec 2009 | A1 |
20090327581 | Coulson | Dec 2009 | A1 |
20090327591 | Moshayedi | Dec 2009 | A1 |
20100017650 | Chin et al. | Jan 2010 | A1 |
20100023674 | Aviles | Jan 2010 | A1 |
20100050053 | Wilson et al. | Feb 2010 | A1 |
20100082890 | Heo et al. | Apr 2010 | A1 |
20100122019 | Flynn et al. | May 2010 | A1 |
20100128537 | Suhail et al. | May 2010 | A1 |
20100138592 | Cheon | Jun 2010 | A1 |
20100165689 | Rotbard et al. | Jul 2010 | A1 |
20100169541 | Freikorn | Jul 2010 | A1 |
20100172179 | Gorobets et al. | Jul 2010 | A1 |
20100174845 | Gorobets et al. | Jul 2010 | A1 |
20100217898 | Priborsky et al. | Aug 2010 | A1 |
20100217915 | O'Connor et al. | Aug 2010 | A1 |
20100223531 | Fukutomi et al. | Sep 2010 | A1 |
20100228928 | Asnaashari et al. | Sep 2010 | A1 |
20100262792 | Hetzler et al. | Oct 2010 | A1 |
20100262795 | Hetzler et al. | Oct 2010 | A1 |
20100262875 | Hetzler et al. | Oct 2010 | A1 |
20100287328 | Feldman et al. | Nov 2010 | A1 |
20100293367 | Berke et al. | Nov 2010 | A1 |
20100312954 | Jeon et al. | Dec 2010 | A1 |
20100318719 | Keays et al. | Dec 2010 | A1 |
20100325340 | Feldman et al. | Dec 2010 | A1 |
20100332726 | Wang | Dec 2010 | A1 |
20110002224 | Tamura | Jan 2011 | A1 |
20110016239 | Stenfort | Jan 2011 | A1 |
20110055455 | Post | Mar 2011 | A1 |
20110055468 | Gonzalez et al. | Mar 2011 | A1 |
20110066788 | Eleftheriou et al. | Mar 2011 | A1 |
20110072423 | Fukata | Mar 2011 | A1 |
20110078393 | Lin | Mar 2011 | A1 |
20110099342 | Ozdemir | Apr 2011 | A1 |
20110107144 | Ohara | May 2011 | A1 |
20110131365 | Zhang et al. | Jun 2011 | A1 |
20110131447 | Prakash et al. | Jun 2011 | A1 |
20110132000 | Deane et al. | Jun 2011 | A1 |
20110138100 | Sinclair | Jun 2011 | A1 |
20110145473 | Maheshwari | Jun 2011 | A1 |
20110161775 | Weingarten | Jun 2011 | A1 |
20110190963 | Glassl et al. | Aug 2011 | A1 |
20110191522 | Condict et al. | Aug 2011 | A1 |
20110191649 | Lim et al. | Aug 2011 | A1 |
20110209032 | Choi et al. | Aug 2011 | A1 |
20110238892 | Tsai et al. | Sep 2011 | A1 |
20110239088 | Post | Sep 2011 | A1 |
20110258496 | Tseng et al. | Oct 2011 | A1 |
20110314219 | Ulrich et al. | Dec 2011 | A1 |
20110320687 | Belluomini et al. | Dec 2011 | A1 |
20120008401 | Katz et al. | Jan 2012 | A1 |
20120011336 | Saika | Jan 2012 | A1 |
20120023144 | Rub | Jan 2012 | A1 |
20120047318 | Yoon et al. | Feb 2012 | A1 |
20120047320 | Yoo et al. | Feb 2012 | A1 |
20120047409 | Post et al. | Feb 2012 | A1 |
20120066450 | Yochai et al. | Mar 2012 | A1 |
20120079348 | Naeimi | Mar 2012 | A1 |
20120079355 | Patapoutian et al. | Mar 2012 | A1 |
20120096217 | Son et al. | Apr 2012 | A1 |
20120124046 | Provenzano | May 2012 | A1 |
20120124273 | Goss et al. | May 2012 | A1 |
20120151260 | Zimmermann et al. | Jun 2012 | A1 |
20120170365 | Kang et al. | Jul 2012 | A1 |
20120185706 | Sistla et al. | Jul 2012 | A1 |
20120213004 | Yun et al. | Aug 2012 | A1 |
20120216085 | Weingarten et al. | Aug 2012 | A1 |
20120236656 | Cometti | Sep 2012 | A1 |
20120239858 | Melik-Martirosian | Sep 2012 | A1 |
20120254686 | Esumi et al. | Oct 2012 | A1 |
20120266011 | Storer et al. | Oct 2012 | A1 |
20120266048 | Chung et al. | Oct 2012 | A1 |
20120278530 | Ebsen | Nov 2012 | A1 |
20120278531 | Horn | Nov 2012 | A1 |
20120284587 | Yu et al. | Nov 2012 | A1 |
20120297113 | Belluomini et al. | Nov 2012 | A1 |
20120311402 | Tseng et al. | Dec 2012 | A1 |
20120317334 | Suzuki et al. | Dec 2012 | A1 |
20120324191 | Strange et al. | Dec 2012 | A1 |
20120331207 | Lassa et al. | Dec 2012 | A1 |
20130007380 | Seekins et al. | Jan 2013 | A1 |
20130007543 | Goss et al. | Jan 2013 | A1 |
20130054881 | Ellis et al. | Feb 2013 | A1 |
20130060994 | Higgins et al. | Mar 2013 | A1 |
20130061019 | Fitzpatrick et al. | Mar 2013 | A1 |
20130073788 | Post et al. | Mar 2013 | A1 |
20130073797 | Chowdhury | Mar 2013 | A1 |
20130074093 | Gounares et al. | Mar 2013 | A1 |
20130080691 | Weingarten et al. | Mar 2013 | A1 |
20130094289 | Sridharan et al. | Apr 2013 | A1 |
20130100600 | Yin et al. | Apr 2013 | A1 |
20130104005 | Weingarten et al. | Apr 2013 | A1 |
20130124792 | Melik-Martirosian et al. | May 2013 | A1 |
20130151753 | Jeon et al. | Jun 2013 | A1 |
20130198436 | Bandic et al. | Aug 2013 | A1 |
20130205102 | Jones et al. | Aug 2013 | A1 |
20130219248 | Sakurai | Aug 2013 | A1 |
20130232290 | Ish et al. | Sep 2013 | A1 |
20130238833 | Vogan et al. | Sep 2013 | A1 |
20130265825 | Lassa | Oct 2013 | A1 |
20130304998 | Palmer | Nov 2013 | A1 |
20130326116 | Goss et al. | Dec 2013 | A1 |
20130332791 | Chu | Dec 2013 | A1 |
20140036589 | Parthasarathy et al. | Feb 2014 | A1 |
20140059359 | Bahirat | Feb 2014 | A1 |
20140108891 | Strasser et al. | Apr 2014 | A1 |
20140129874 | Zaltsman et al. | May 2014 | A1 |
20140158525 | Greene | Jun 2014 | A1 |
20140181370 | Cohen et al. | Jun 2014 | A1 |
20140208174 | Ellis et al. | Jul 2014 | A1 |
20140258769 | Baryudin et al. | Sep 2014 | A1 |
20140372777 | Reller et al. | Dec 2014 | A1 |
Number | Date | Country |
---|---|---|
1 956 489 | Aug 2008 | EP |
1 990 921 | Nov 2008 | EP |
2 498 259 | Sep 2012 | EP |
2012129859 | Jul 2012 | JP |
WO 2009042298 | Apr 2009 | WO |
WO 2011156466 | Dec 2011 | WO |
Entry |
---|
Ulintech, “ATA Command Table (in Alphabetic Order),” Feb. 6, 2011, https://web.archive.org/web/20110206060820/http://www.ulinktech.com/downloads/AT. 6 pages. |
International Search Report dated Mar. 25, 2014, received in International Patent Application No. PCT/US2013/072400, which corresponds to U.S. Appl. No. 13/690,337, 3 pages (Ellis) |
Invitation to Pay Additional Fees dated Jul. 25, 2014, received in International Patent Application No. PCT/US2014/021290, which corresponds to U.S. Appl. No. 13/791,797, 8 pages (Dean). |
International Search Report and Written Opinion dated Jul. 31, 2014, received in International Patent Applicatlon No. PCT/US2014/031465, which corresponds to U.S. Appl. No. 13/851,928,13 pages (Ellis). |
International Search Report and Written Opinion dated Jul. 31, 2014, received in International Patent Application No. PCT/US2014/033876, which corresponds to U.S. Appl. No. 13/861,326, 9 pages (Fitzpatrick). |
International Search Report and Written Opinion dated Nov. 7, 2014, received in International Patent Application No. PCT/US2014/049732, which corresponds to U.S. Appl. No. 14/334,350, 13 pages (Fitzpatrick). |
International Search Report and Written Opinion dated Oct. 17, 2014, received in International Patent Application No. PCT/US2014/049734, which correpsonds to U.S. Appl. No. 14/332,359, 8 pages (Higgins). |
International Search Report and Written Opinion dated Oct. 23, 2014, received in International Patent Application No. PCT/US2014/049736, which corresponds to U.S. Appl. No. 14/446,249, 8 pages (Fitzpatrick). |
International Search Report and Written Opinion dated Nov. 5, 2014, received in International Patent Application No. PCT/US2014/049282, which corresponds to U.S. Appl. No. 13/957,407, 12 pages (Fitzpatrick). |
Tseng et al., “Understanding the Impact of Power Loss on Flash Memory,” DAC'11, Jun. 5-10, 2011, San Diego, California, 6 pages. |
International Search Report and Written Opinion dated Aug. 22, 2014, received in International Patent Application No. PCT/US2014/032978, which corresponds to U.S. Appl. No. 14/081,992, 10 pages (Ellis). |
Cooke, “Introduction to Flash Memory (T1A),” Flash Memory Summit, Aug. 22, 2008, Micron Technology, Inc., 102 pages. |
Gal et al., “Algorithms and Data Structures for Flash Memories,” ACM Computing Surveys, Jun. 2005, vol. 37, No. 2, 30 pages. |
IBM Corporation, “Systems Management, Work Management,” Version 5, Release 4, 9th Edition, Feb. 2006, pp. 1-21. |
Spanjer, “Flash Management—Why and How?” Smart Modular Technologies, Nov. 2009, http://www.scantec.de/fileadmin/pdf/Smart_Modular/Flash-Management.pdf, 14 pages. |
Texas Instruments, “Power Management IC for Digital Set Top Boxes,” SLVSA10A, Sep. 2009, pp. 1-22. |
International Search Report and Written Opinion dated Dec. 20, 2013, received in PCT/US2013/045282, which corresponds to U.S. Appl. No. 13/493,949, 7 pages (Ellis). |
International Search Report and Written Opinion dated Jun. 12, 2014, received in PCT/US2014/018972, which corresponds to U.S. Appl. No. 13/779,352, 12 pages (Schmier). |
International Search Report and Written Opinion dated May 14, 2014, received in International Patent Application No. PCT/US2014/017168, which corresponds to U.S. Appl. No. 14/076,115, 6 pages (Fitzpatrick). |
International Search Report and Written Opinion dated May 14, 2014, received in International Patent Application No. PCT/US2014/017169, which corresponds to U.S. Appl. No. 14/076,148, 6 pages (Fitzpatrick). |
Obrien, “SMART Storage Systems Optimus SAS Enterprise SSD Review”, “StorageReview.com”, Oct. 9, 2012, pp. 1-44. |
Narayanan et al., “Migrating Server Storage to SSDs: Analysis of Tradeoffs,” Computer Systems, Apr. 2009, 12 pages. |
Shiraz et al., “Block Aging Prevention Technique (BAP) for Flash Based Solict State Disks,” 7th International Conference on Emerging Technologies (ICET), Sep. 5, 2011, 6 pages. |
Tai et al, “Prolongation of Lifetime and the Evaluation Method of Dependable SSD,” 25 International Symposium on Defect and Fault Tolerance in VLSI Systems, 2010, NJ, USA, 8 pages. |
Yimo et al., “WeLe-RAID: A SSD-Based RAID for System Endurance and Performance,” Jan. 2011, Network and Parallel Computing, Springer, 14 pages. |
International Search Report and Written Opinion dated Jan. 9, 2035, received in International Patent Application No. PCT/US2014/049731, which corresponds to U.S. Appl. No. 14/334,324, 9 pages (Fitzpatrick). |
International Search Report and Written Opinion dated Feb. 18, 2015, received in International Patent Application No. PCT/US2014/065401, which corresponds to U.S. Appl. No. 14/081,031, 9 pages (Higgins). |
International Search Report dated Apr. 15, 2014, received in International Patent Application No. PCT/US2013/078340, which corresponds to U.S. Appl. No. 13/746,542, 11 pages (Ellis). |
Online Merriam Webster Dictionary, definition of “Distinct” from Jun. 12, 2011, https://web.archive.org/web/20110612181129/http://www2.merriam-webster.com/cgi-bin/mwdictadu?book=Dictionary&va=distinct. |
Number | Date | Country | |
---|---|---|---|
20140310494 A1 | Oct 2014 | US |