Patent Application
20240385671
This patent document can be exactly reproduced as it appears in the files of the United States Patent and Trademark Office, but the assignee(s) otherwise reserves all rights in any subsets of included original works of authorship in this document protected by 17 USC 102(a) of the U.S. copyright law.
In the following Background, Summary, and Detailed Description, paragraph headings are signifiers that do not limit the scope of an Embodiment of a Claimed Invention (ECIN). The citation or identification of any publication signifies neither relevance nor use as prior art. A paragraph for which the font is all italicized signifies text that exists in one or more patent specifications filed by the assignee(s). A writing enclosed in double quotes (“ ”) signifies an exact copy of a writing that has been expressed as a work of authorship. Signifiers, such as a word or a phrase enclosed in single quotes (‘ ’), signify a term that as of yet has not been defined and that has no meaning to be evaluated for, or has no meaning in that specific use (for example, when the quoted term ‘module’ is first used) until defined.
This disclosure has general significance in the field of power management in processors, in particular, the synthesis of clock waveforms for more efficient power management in high-speed processors. This information is limited to use in the searching of the prior art.
The operating frequency of a computer processor's system clock fundamentally impacts key performance metrics such as latency, throughput, peak power, energy required to perform a computation, and the rate of change of power supply load current. Common methods of manipulating the frequency of the clock generator, such as setting the clock frequency of a processor to a particular value during execution of an entire algorithm, may lack sufficient granularity or responsiveness to fully optimize system performance metrics.
Integrated circuits, such as tensor and graphical processors, typically operate in several different modes such as high computational activity, low computational activity, and quiescent or sleep state. Overall system performance optimization requires different clock waveforms for each different mode, but dynamically changing the clock frequency has many limitations and incurs substantial implementation and operational costs, especially in the common situation where Phase-Locked Loop (PLL) techniques are incorporated in the clock generator. For example, clock frequency synthesis controllers often have coarse granularity and can provide only a relatively small number of discrete operating frequencies. The switchover mechanism must guarantee waveform integrity during all clock phases, so switching to a different frequency may take several clock cycles. Changing the PLL reference clock frequency or multiplier value may produce indeterminate waveforms for many cycles as the PLL attempts to lock in on new reference conditions. A clock waveform generator that overcomes these limitations would enable improved integrated circuit performance.
This Summary, together with any Claims, is a brief set of signifiers for at least one ECIN (which can be a discovery, see 35 USC 100(a); and see 35 USC 100(j)), for use in commerce for which the Specification and Drawings satisfy 35 USC 112.
In one or more ECINs disclosed herein, clock period synthesis (CPS) methods are disclosed that enable shorter runtime latency, higher computational job throughput, more efficient power management, and a lower implementation cost than existing clock waveform methods for high-speed processors.
In some embodiments of the ECINs disclosed herein, the clock period is increased or decreased, which saves energy more efficiently than inserting ‘No Operation’ instructions (NOPs), and which also makes it easier to enable software support in the compiler.
In some embodiments of the ECINs disclosed herein, the CPS methods to be used can be specified by the user in a Service Level Agreement (SLA), for example, with the use specifying a clock period and waveform that minimizes power consumption, that reduces peak consumption, or that minimizes time of execution of the algorithm. In other embodiments, some CPS methods are scheduled by a compiler and enabled by the processor during execution when an upcoming power problem is anticipated.
In some embodiments of the ECINs disclosed herein, the CPS circuit comprises a digital logic circuit that generates a unique clock waveform (period and duty cycle) for each individual instruction or operational cycle of a processor. The ability to provide a different clock waveform during the operation of each individual instruction cycle enables: a) faster operational performance by using the shortest period that satisfies instruction-specific timing constraints, b) a simple mechanism for reducing peak power on a per-cycle or cycle-aggregate basis, c) a simple mechanism for limiting the di/dt slope for changes in load current, and d) the ability to optimize performance and yield by adjusting the duty cycle according to instruction-specific needs.
In some embodiments of the ECINs disclosed herein, CPS reuses the same shift register sequential elements for the clock high time and clock low time, and for edges that start or end on the rising or falling edge of the high-speed clock.
In some embodiments of the ECINs disclosed herein, the CPS uses an efficient activation mechanism to provide half-cycle resolution of the high frequency clock period, in contrast to traditional approaches that operate at only the coarser resolution of the full-cycle high frequency clock period.
This Summary does not completely signify any ECIN. While this Summary can signify at least one essential element of an ECIN enabled by the Specification and Figures, the Summary does not signify any limitation in the scope of any ECIN.
The following Detailed Description, Figures, and Claims signify the uses of and progress enabled by one or more ECINs. All of the Figures are used only to provide knowledge and understanding and do not limit the scope of any ECIN. Such Figures are not necessarily drawn to scale. A brief list of Figures is below.
The Figures can have the same, or similar, reference signifiers in the form of labels (such as alphanumeric symbols, e.g., reference numerals), and can signify a similar or equivalent function or use. Further, reference signifiers of the same type can be distinguished by appending to the reference label a dash and a second label that distinguishes among the similar signifiers. If only the first label is used in the Specification, its use applies to any similar component having the same label irrespective of any other reference labels.
In the Figures, reference signs can be omitted as is consistent with accepted engineering practice; however, a skilled person will understand that the illustrated components are understood in the context of the Figures as a whole, of the accompanying writings about such Figures, and of the embodiments of the claimed inventions.
The Figures and Detailed Description, only to provide knowledge and understanding, signify at least one ECIN. To minimize the length of the Detailed Description, while various features, structures or characteristics can be described together in a single embodiment, they also can be used in other embodiments without being written about. Variations of any of these elements, and modules, processes, machines, systems, manufactures or compositions disclosed by such embodiments and/or examples are easily used in commerce. The Figures and Detailed Description signify, implicitly or explicitly, advantages and improvements of at least one ECIN for use in commerce.
In the Figures and Detailed Description, numerous specific details can be described to enable at least one ECIN. Any embodiment disclosed herein signifies a tangible form of a claimed invention. To not diminish the significance of the embodiments and/or examples in this Detailed Description, some elements that are known to a skilled person can be combined together for presentation and for illustration purposes and not be specified in detail. To not diminish the significance of these embodiments and/or examples, some well-known processes, machines, systems, manufactures or compositions are not written about in detail. However, a skilled person can use these embodiments and/or examples in commerce without these specific details or their equivalents. Thus, the Detailed Description focuses on enabling the inventive elements of any ECIN. Where this Detailed Description refers to some elements in the singular tense, more than one element can be depicted in the Figures and like elements are labeled with like numerals.
The user device 102 comprises any electronic computing device, such as a personal computer, laptop, or workstation, which uses an Application Program Interface (API) 104 to construct programs to be run on the processor 120. The server 110 receives a program specified by the user at the user device 102, and compiles the program to generate a compiled program 114. In some embodiments, a compiled program 114 enables a data model for predictions that processes input data and makes a prediction from the input data. Examples of predictions are category classifications made with a classifier, or predictions of time series values. In some embodiments, the prediction model describes a machine learning model that includes nodes, tensors, and weights. In one embodiment, the prediction model is specified as a TensorFlow model, the compiler 112 is a TensorFlow compiler and the processor 120 is a tensor processor. In another embodiment, the prediction model is specified as a PyTorch model, the compiler is a PyTorch compiler. In other embodiments, other machine learning specification languages and compilers are used. For example, in some embodiments, the prediction model defines nodes representing operators (e.g., arithmetic operators, matrix transformation operators, Boolean operators, etc.), tensors representing operands (e.g., values that the operators modify, such as scalar values, vector values, and matrix values, which may be represented in integer or floating-point format), and weight values that are generated and stored in the model after training. In some embodiments, where the processor 120 is a tensor processor having a functional slice architecture, the compiler 112 generates an explicit plan for how the processor will execute the program, by translating the program into a set of operations that are executed by the processor 120, specifying when each instruction will be executed, which functional slices will perform the work, and which stream registers will hold the operands. This type of scheduling is known as “deterministic scheduling”. This explicit plan for execution includes information for explicit prediction of excessive power usage by the processor when executing the program.
The assembler 116 receives compiled programs 114, generated by the compiler 112, and performs final compilation and linking of the scheduled instructions to generate a compiled binary. In some embodiments, the assembler 114 maps the scheduled instructions indicated in the compiled program 112 to the hardware of the server 110, and then determines the exact component queue in which to place each instruction.
The processor 120, e.g., is a hardware device with a massive number of matrix multiplier units that accepts a compiled binary assembled by the assembler 116, and executes the instructions included in the compiled binary. The processor 120 typically includes one or more blocks of circuity for matrix arithmetic, numerical conversion, vector computation, short-term memory, and data permutation/switching. Once such processor 120 is a tensor processor having a functional slice architecture. In some embodiments, the processor 120 comprises multiple tensor processors connected together.
The functional units of processor 200 (also referred to as “functional tiles”) are aggregated into a plurality of functional process units (hereafter referred to as “slices”) 205, each corresponding to a particular function type in some embodiments. For example, different functional slices of the processor correspond to processing units for MEM (memory), VXM (vector execution module), MXM (matrix execution module), NIM (numerical interpretation module), and SXM (switching and permutation module). In other embodiments, each tile may include an aggregation of functional units such as a tile having both MEM and execution units by way of example. As illustrated in
Processor 200 also includes communication lanes to carry data between the functional units of different slices. Each communication lane connects to each of the slices 205 of processor 200. In some embodiments, a communication lane 220 that connects a row of functional units of adjacent slices is referred to as a “super-lane”, and comprises multiple data lanes, or “streams”, each configured to transport data values along a particular direction. For example, in some embodiments, each functional unit of processor 200 is connected to corresponding functional units on adjacent slices by a super-lane made up of multiple lanes. In other embodiments, processor 200 includes communication devices, such as a router, to carry data between adjacent functional units.
By arranging the functional units of processor 200 into different functional slices 205, the on-chip instruction and control flow of processor 200 is decoupled from the data flow. Since many types of data are acted upon by the same set of instructions, what is important for visualization is visualizing the flow of instructions, not the flow of data. For some embodiments,
In some embodiments, the functional units in the same slice execute instructions in a ‘staggered’ fashion where instructions are issued tile-by-tile within the slice over a period of N cycles. For example, the ICU for a given slice may, during a first clock cycle, issues an instruction to a first tile of the slice (e.g., the bottom tile of the slice as illustrated in
The functional slices of the processor are arranged such that operand data read from a memory slice is intercepted by different functional slices as the data moves across the chip, and results flow in the opposite direction where they are then written back to memory. For example, a first data flow from a first memory slice flows in a first direction (e.g., towards the right), where it is intercepted by a VXM slice that performs a vector operation on the received data. The data flow then continues to an MXM slice which performs a matrix operation on the received data. The processed data then flows in a second direction opposite from the first direction (e.g., towards the left), where it is again intercepted by a VXM slice to perform an accumulate operation, and then written back to the memory slice.
In some embodiments, the functional slices of the processor are arranged such that data flow between memory and functional slices occur in both the first and second directions. For example, a second data flow originating from a second memory slice that travels in the second direction towards a second slice, where the data is intercepted and processed by a VXM slice before traveling to the second MXM slice. The results of the matrix operation performed by the second MXM slice then flow in the first direction back towards the second memory slice.
In some embodiments, stream registers are located along a super-lane of the processor. The stream registers are located between functional slices of the processor to facilitate the transport of data (e.g., operands and results) along each super-lane. For example, within the memory region of the processor, stream registers are located between sets of four MEM units. The stream registers are architecturally visible to the compiler, and serve as the primary hardware structure through which the compiler has visibility into the program's execution. Each functional unit of the set contains stream circuitry configured to allow the functional unit to read or write to the stream registers in either direction of the super-lane. In some embodiments, each stream register is implemented as a collection of registers, corresponding to each stream of the super-lane, and sized based upon the basic data type used by the processor (e.g., if the TSP's basic data type is an INT8, each register may be 8-bits wide). In some embodiments, in order to support larger operands (e.g., FP16 or INT32), multiple registers are collectively treated as one operand, where the operand is transmitted over multiple streams of the super-lane.
All of these functional features—superlanes of functional units, slices of instruction flow, handling of different types of integers and floating-point numbers, occurring trillions of times a second, create complicated power flows and possible disruptive power fluctuations that could negatively impact the performance of the processor. However, given the deterministic nature of executions by the processor, any disruptive power fluctuations (such as voltage droop) can be determined before execution of the program, with information (such as processor instructions, and timing for such instructions) about such fluctuations being supplied by the compiler to the processor, for the processor to use during program execution to mitigate the fluctuations.
In some of the ECINs disclosed here, clock period synthesis is used to achieve more efficient power management in a processor, especially tensor and graphical processors which perform billions and trillions of floating-point operations per second. A large number of such operations that are executed at the same time, or nearly at the same time, can create potentially damaging electric current flows in the processor, which can cause heat flows that are damaging, making it important to minimize changes in current flow (di/dt) during execution of a program.
In some of the ECINs disclosed herein, clock period synthesis is enabled by adding additional hardware and software instructions to a processor.
In some of the ECINs disclosed herein, the processor comprises the following four elements: a High Frequency Clock (HFC) generated by an on-chip Phase-Locked Loop (PLL) circuit where the period of the HFC is preferably shorter than the nominal period of the main clock (ChipClock) period; a waveform generator to produce the more useful ChipClock waveforms disclosed herein using high-speed shift registers; clock period duration logic to preload values for waveform generation; and an instruction control unit (ICU) to provide instructions for the CPS methods disclosed herein.
ChipClock waveform resolution typically is half of the HFC period, representing the smallest increment of change for the ChipClock period. The duration of half of the HFC period is called the High Frequency Clock Phase Period (HFCPP). For example, the HFC period for the TSP tensor processor from Groq, Inc., is about 27.78 picoseconds. Half-cycle waveform resolution is enabled with only a tiny incremental circuit area and power cost is a useful advantage of some of the ECINs.
As an example, an HFC period that is one-eighth the nominal ChipClock period enables an HFCPP that is 1/16th of the nominal ChipClock period. This HFCPP enables a clock period waveform resolution granularity of plus-or-minus 6.25%.
ChipClock periods that are enabled are integer multiples of the HFCPP. The multiple does not need to be a power of two. The chip reset signal sets the ChipClock period to the Default ChipClock duration. The DefaultChipClock period can be overwritten using a configuration register. The configuration register also has a MinClockPeriod field which is the minimum number of HFCPP periods allowed for ChipClock, and a EnableClockChange flag that prohibits any ChipClock period changes. The default value of the MinClockPeriod minimum ChipClock period register is equal to the hardware value of the DefaultChipClock period. The DefaultChipClock period should never be set to a value less than the MinClockPeriod. The default value of the EnableClockChange flag is FALSE to prohibit clock period changes until a configuration register write operation sets the value of the flag to TRUE. After the processor has booted (restarted) and a program is running, if the EnableClockChange flag is set to TRUE, ChipClock period changes are determined exclusively by subsequent software instructions, and a configuration register write operation should not be used to change the period until after the user instructions have completed.
The minimum ChipClock period is eight times the HFCPP, where the minimum ChipClock high time (the amount of time the clock is in the high state, and the duty cycle is the percentage of the clock is high) is four times the HFCPP, and the minimum low time is four times the HFCPP, forming a waveform with a 50/50 duty cycle. The minimum ChipClock period constraint implies that the HFC period should be less than or equal to one-fourth of the shortest ChipClock period that will be used. That is, the HFC frequency is at least four times the frequency of the fastest ChipClock frequency that is used.
The longest possible ChipClock period is limited by either the maximum size of the Target ChipClock Period field in the instruction format which supports the use of up to 2{circumflex over ( )}9=512 HFCPP long clock periods, or by the number of shift register stages implemented in the CPS high-speed shift register, whichever is smaller. The instruction format and CPS high-speed shift register properties are described in respective sections below. The CPS high-speed shift register operates at a much higher speed than traditional approaches (using counters or Finite State Machines) because there are no extra logic elements between the sequential elements. These circuits disclosed herein with fewer logic levels can operate at higher speeds.
In some of the ECINs disclosed herein, processor current flow changes (di/dt) are managed by setting the Slope, Steep, and Linear fields in a CPS instruction word to values that increase or decrease the rate of change of the current drawn by the processor per unit time. This capability is used to control the rate of change in load current imposed on the voltage regulator during large step increases in load current, or during large release reductions in load current (when fewer instructions are being executed).
When Linear=0 and Steep=0, the ChipClock period is increased or decreased by another unit of HFCPP after each time Slope ChipClock periods have been completed, until the ChipClock period equals the TargetPeriod. A larger Slope value will cause the di/dt value to be smaller. When Steep=0, Rise=1, and Run=Slope, the Ramp angle=Rise/Run.
When Linear=0 and Steep=1, the ChipClock period is increased or decreased by Slope units of HFCPP after each ChipClock period has been completed, until the ChipClock period equals the TargetPeriod. A larger Slope value will cause the di/dt value to be larger. When Steep=1, Rise=Slope, and Run=1, the Ramp angle=Rise/Run.
When Linear=1, Steep=0 and Slope=1, the ChipClock period is increased or decreased slowly in a way that limits the di/dt change to a small fixed value. The change in ChipClock period from one period to a new period that is one HFCPP unit larger or smaller is spread across several blocks on ChipClock periods so that the average di/dt during each block of ChipClock periods is smaller than some specified di/dt limit value. For example, if the current ChipClock period is 13 HFCPP units and the target new ChipClock period is 14 HFCPP units, the di/dt step change would equal one divided by 13, or 7.69%. Assuming a specification that di/dt must not exceed 1%, then the period transition from 13 to 14 must be spread over Ceiling(7.69)=8 blocks, where each block is 8 ChipClock periods long, and the duration of each ChipClock period in each block is either 13 or 14, and the number of ChipClock periods that are 14 in each block increases by one for each block moving from all 13 to all 14 after 8 blocks. The position of each shorter or longer period is chosen to be spread out as much as possible to minimize the local average change over any interval of ChipClock periods.
With adequate timing information describing different timing support for different subsets of instructions, the compiler can identify sets of instruction cycles that may operate at a shorter clock period than other instruction sets.
To exploit this opportunity, the hardware design process for a processor that uses CPS runtime acceleration needs to include additional timing closure activities. For example, a processor designer partitions the chip into several subsets of instructions or circuit operations. At least one of these partitions is designed to run faster than at least one other partition that runs slower. The processor designer uses Static Timing Analysis (STA) for timing closure, which means that all circuit timing properties are verified to satisfy applicable timing constraints. The designer closes timing, for example, at 1.1 GHz for the slower partition, and closes timing at 1.2 GHz for the faster partition. The designer should give special attention when closing timing on a circuitry subset of the chip, to prevent any metastability-triggering situations.
Prior to, or during execution, the ChipClock period is configured to satisfy the most stringent requirements of any instruction that is active. This may be done in the processor instruction sequence compiler prior to execution, or it may be done by a circuit or processor during runtime execution. An active instruction is either a newly dispatched instruction, or the subsequent cycles of a multi-cycle instruction that was dispatched previously. For example, the ChipClock period is set to the longest period required by any active instruction. If all active instructions are in the faster partition for certain clock cycles, then the chip will run faster than during other clock cycles when some active instructions are from the slower partition.
A relatively small number of logic gates are required for CPS.
Also depicted in
The period of the high frequency clock and the number of shift register stages required for CPS are together determined by the nominal ChipClock period, the desired waveform granularity, and the maximum desired clock period for low power operating modes. For example, with a nominal 1 nS ChipClock period, 6.25% waveform granularity, and a maximum ChipClock period that is 16 times the nominal ChipClock period, the number of shift register stages required would be as follows.
The duration of HFCPP is the ChipClock period times the waveform granularity percentage, for example, 1 nS*6.25%=0.0625 nS (nanoseconds). The period of the HFC is two times the duration of HFCPP, which here equals 2*0.0625 nS=0.125 nS, so the HFC would be 8 GHz. The number of shift register stages required is the maximum ChipClock period divided by the HFC period, or 16 nS/0.125 nS=128 DFF stages, plus a few extra DFFs to implement one HFCPP resolution.
In
CPS instructions are intentionally orthogonal to other functional instructions, which means that the functional instruction sequence is scheduled by the compiler or human programmer without consideration of CPS instructions, and then CPS instructions are determined by an efficient post-processing operation based on the available instruction sequence. This orthogonality facilitates much faster program compilation than would be possible if power requirements were applied as constraints during the determination of the optimized instruction sequence. In an alternative embodiment, CPS instructions are determined in conjunction with the functional instruction sequence. CPS instructions can dispatch as often as once per ChipClock. In the absence of any CPS instructions for a job, the ChipClock period defaults to a default value at boot time. A configuration register write can be used to overwrite the HW default ChipClock period. Chip Reset sets the ChipClock period to the default value. Cumulative clock periods are aligned at data transfer times, which should be considered invariant during instruction scheduling by the compiler. The Compiler should keep a tally of the real-time duration of the instructions executed on each chip in a multi-TSP system. The real-time values should be deterministically aligned at data transfer times. The Compiler has a great deal of flexibility to optimize clock durations on each individual processor, although the longest duration required during each synchronization interval will dominate.
Software control of ChipClock periods is achieved by configuring eight four CPS instruction parameter values: TargetPeriod, Slope, Steep, and Linear, MostlyHi, ExtraLong, Lengthenable, and Shortenable. All eight four parameters are set in each instruction. The TargetPeriod specifies the number of HFCPP periods that will be in each ChipClock period. The Slope, Steep, and Linear fields determine how the current period changes to the TargetPeriod for each intervening clock cycle according to the descriptions in the preceding and following paragraphs. The high time duration is greater-than or equal to the low time duration if the MostlyHi bit is set true in the CPS instruction. If the ExtraLong field has a value greater than zero, then high time is increased in duration by the value of ExtraLong number of HFCPP intervals when MostlyHi is true. The low time duration is greater-than or equal to the high time duration if the MostlyHi bit is set false in the CPS instruction. If the ExtraLong field has a value greater than zero, then low time is increased in duration by the value of ExtraLong number of HFCPP intervals when MostlyHi is false. The sum of the high time plus the low time is equal to the period of the clock cycle. CPS instructions are configured to operate with an asymmetric duty cycle for circuits such as memory arrays, clock gating logic, analog circuits, etc. that require an asymmetric duty cycle for optimized operation. The Lengthenable field is set true for clock periods that are eligible to be lengthened for the purpose of aligning the timing of inter-chip deterministic events. The Shortenable field is set true for clock periods that are eligible to be shortened for the purpose of aligning the timing of inter-chip deterministic events.
To control processor current flow changes, di/dt, it is desirable to spread out changes in the magnitude of current drawn by the processor. The Slope, Steep, and Linear parameters specify the size of the incremental steps taken during each ChipClock period change while transitioning from the current value of ChipClock to the TargetPeriod.
The CPS instruction word format uses 9 bits (shown as Bit Positions 29 through 21 in the above example CPS Instruction Word Format table) for the TargetPeriod field, e.g., bits 21 to 29.
New CPS Instructions immediately preempt previously dispatched instructions, even if the ChipClock period is not yet equal to the TargetPeriod specified in the previous instruction (e.g., the ChipClock period is still changing). Extra care is advised when the Compiler calculates the timing consequences of a preempted CPS instruction.
The Linear field linearizes di/dt as the ChipClock period increases or decreases for small values of the ChipClock period. Without linearization, di/dt would be much larger for each change in ChipClock period for smaller ChipClock period durations. The pattern is a concave curve that has the functional shape of 1/x. By reducing the di/dt for smaller ChipClock periods, the di/dt is linearized, as shown in the Linearization Plot and the Linearization Table below.
Linearization is activated when (Linear==1 AND Steep==0 AND Slope==0), causing the CPS FSM to emit a preselected sequence of period values from a stored table. The number of period values to linearize a transition is equal to the square of the Linearization Block (LB) size. LB size is determined by the ceiling of the ratio of the largest percentage change to or from the TargetPeriod divided by the desired maximum change size. In an ECIN where the minimum clock duration is 8 HFCC intervals, a change to this TargetPeriod value will have a maximum step size of ⅛=12.5%. If the maximum change size is 1%, then LB=the ceiling of (12.5%/1%)=13. For all other TargetPeriod values, LB=CEILING(1/(TargetPeriod−1)/MaxStepSize). Calculated LB values are shown in the table below.
The ability to set safe and reliable operating conditions is essential for electrical systems. In one ECIN, for TSP processors available from Groq, the main operating Vdd voltage for the processor can be changed via the Board Management Controller (BMC) using a PCB microcontroller that interfaced with the voltage regulators through Serial Peripheral Interface (SPI) bus ports, and similarly the PCB clock generator frequency can be set to provide an appropriate reference clock frequency for the on-chip PLL. Changes to Vdd or the Reference Clock Frequency are made between jobs. Changing the external Reference Clock Frequency while the TSP is operating is not advised because invalid clock periods may result as the PLL tracks to lock-in on the new reference clock frequency. In the best case, if the TSP continued to operate, the latency would be indeterminate because PLL tracking has significant uncertainty, and the power would also be less predictable due to the changing clock frequency. Power levels would also be uncertain during the time it takes a Vdd level change to propagate through the voltage regulator to slew the output voltage to the new setpoint.
The above-described embodiments mostly enable clock period synthesis for a single processor. CPS for multiply-connected deterministic processors requires additional synchronization of clocks on different processors.
In operation, the two chips each run part of a program and they may send data to each other. Ideally they would have identical reference clocks and also identical high frequency clocks. Ideally these clocks do not drift over time and they will remain constant. The chip clocks, however, between the two processors do not need to be the same throughout the program. For example, the compiler may intentionally compile a program to have CPS to set chip1 to run at 1 GHz and chip2 to run at 500 MHz. The compiler understands that chip1 runs twice as fast as chip2. When sending and receiving data between the two chips during the runtime of the program, the compiler would take their pre-planned frequency differences into account and schedule the data transfer during the program accordingly in wall-clock time. Even though in this example the two chips run at different constant chip clock frequencies, they do not need to be. The compiler can compile the program for chip1 to say vary from 1 GHz, to 0.9 GHz, down to 0.8 GHz, and back up to 1 GHz. It can also vary chip2 to say from 500 MHz, to 499 MHz, and up to 505 MHz etc. Since the compiler controls and plans when the CPS changes on these clock chip frequencies, it can schedule any data exchanges between these two chips accordingly using common wall-clock time.
In reality, the reference clocks for each processor can oscillate at slightly different frequencies. For example, one processor has a reference clock at 50 Mhz, while the other processor has a reference clock of 50.0001 Mhz as shown in
When the reference clocks of the two chips are different due to their oscillator variance and drifting over time, their PLL generated high frequency clocks will also be slightly different, and their scheduled clock chip frequency will also be slightly different than what the compiler is expecting. After the program runs for a while, the amount of wall-clock time that each chip has run is no longer consistent with what the compiler is expecting. A scheduled data transfer between the two may now be jeopardized (e.g. chip1 sends some data to chip2 and chip2 is supposed to receive it but it is not because its timing is off). Usually the compiler builds in some small amount of cushion to accommodate for a small unexpected mis-alignment from reality. But if the program has run long enough, the misalignment continues to accumulate and at some point, data transfer will fail.
When multiple processors are connected through a set of C2C channels, these processors can be configured as a spanning tree. To compensate for the difference in chip clock frequency than what the compiler is expecting across all these processors, the CPS of the processor at the root of the tree generates a beacon pulse to all of the downstream processors in the tree through the connected C2C communication links. Typically, the beacon pulses are sent at a constant rate, for example, every microsecond which is equivalent to 10000 PLL generated fast clock cycles at 10 GHz.
As seen in
The propagation delay between the CPS circuits and the C2C circuits has a constant delay using a constant source clock generated by the parent CPS. The communication delay is also constant between processors, e.g., between the C2C circuits.
The child CPS counts the number of fast clocks that have elapsed between every pair of beacons being received. Since the child knows how many fast clocks there are in between the beacons that are sent by its parent (e.g. system software would configure this number into a configuration register in the child. In this example, the number would be 10000), if the child receives a beacon a little earlier or a little later than expected, it means that its local fast clock is running a little slower or faster, respectively, compared to its parent. This translates to the child's chip clock is also running a little slower or faster relative to what the compiler is expecting as well. The child CPS circuity then adjusts the chip clock that it generates up and down accordingly every time a beacon is received to continuously compensate for the difference. Any unintentional+/−jitter that a beacon receives (e.g. clock domain crossing on the C2C circuits) would cause the child to over/under compensate by a little, but then this error would be automatically corrected when the subsequent beacon is received.
In one embodiment, the CPS in the child always adjusts its generated chip clock to be faster or slower, in order to compensate for this unexpected frequency difference. For example, if the child receives a beacon after counting 10010 fast clocks, instead of 10000 fast clocks that it expects, after the previous received beacon, this is an indication that its reference clock is running faster than what the compiler is expecting. To compensate, the child CPS then slows down its generated chip clock by a total amount of 10 fast clocks till the next beacon is received. If the child receives a beacon after counting 9990 fast clocks, instead of 10000 fast clocks that it expects, after the previous received beacon, this is an indication that its reference clock is running slower than what the compiler is expecting. To compensate, the child CPS then speeds up its generated chip clock by a total amount of 10 fast clocks till the next beacon is received.
However, sometimes when a chip is manufactured for 1 Ghz operation, it may not be able to run at a higher frequency, e.g. increase to 1.05 Ghz from 1 GHz. Accordingly, in a different embodiment, the root processor of the tree slows its chip clock down and also prolongs the cycle of sending out the beacon accordingly to ensure that it is operating at an effectively lower frequency than the maximum frequency of all the child processor chip clocks. In that case, a child processor only needs to slow down its clocks, and never need to speed up to compensate. For example, if the root's CPS normally sends out a beacon every 10000 fast clocks, it would send out a beacon every 10100 fast clocks. It would also slow down the generation of the chip clock by a total of 100 fast clocks before sending the next beacon. This effectively lets the root give an illusion to its children that it is running slower than it actually is.
For traditional non-deterministic multiprocessor systems where the compiler does not control the executions of instructions, and their timing, small differences in clock signals such as 0.0001 Hz can be ignored without need for this multiple deterministic processor additional clock period synthesis beyond CPS implemented just for power saving.
Data and Information. While ‘data’ and ‘information’ often are used interchangeably (e.g., ‘data processing’ and ‘information processing’), the term ‘datum’ (plural ‘data’) typically signifies a representation of the value of a fact (e.g., the measurement of a physical quantity such as the current in a wire, or the price of gold), or the answer to a question (e.g., “yes” or “no”), while the term ‘information’ typically signifies a set of data with structure (often signified by ‘data structure’). A data structure is used in commerce to transform an electronic device for use as a specific machine as an article of manufacture (see In re Lowry, 32 F.3d 1579 [CAFC, 1994]). Data and information are physical objects, for example binary data (a ‘bit’, usually signified with ‘0’ and ‘1’) enabled with two levels of voltage in a digital circuit or electronic component. For example, data can be enabled as an electrical, magnetic, optical or acoustical signal or state; a quantum state such as a particle spin that enables a ‘qubit’; or a physical state of an atom or molecule. All such data and information, when enabled, are stored, accessed, transferred, combined, compared, or otherwise acted upon, actions that require and dissipate energy.
As used herein, the term ‘process’ signifies an artificial finite ordered set of physical actions (‘action’ also signified by ‘operation’ or ‘step’) to produce at least one result Some types of actions include transformation and transportation. An action is a technical application of one or more natural laws of science or artificial laws of technology. An action often changes the physical state of a machine, of structures of data and information, or of a composition of matter. Two or more actions can occur at about the same time, or one action can occur before or after another action, if the process produces the same result. A description of the physical actions and/or transformations that comprise a process are often signified with a set of gerund phrases (or their semantic equivalents) that are typically preceded with the signifier ‘the steps of’ (e.g., “a process comprising the steps of measuring, transforming, partitioning and then distributing . . . ”). The signifiers ‘algorithm’, ‘method’, ‘procedure’, ‘(sub)routine’, ‘protocol’, ‘recipe’, and ‘technique’ often are used interchangeably with ‘process’, and 35 U.S.C. 100 defines a “method” as one type of process that is, by statutory law, always patentable under 35 U.S.C. 101. As used herein, the term ‘thread’ signifies a subset of an entire process. A process can be partitioned into multiple threads that can be used at or about at the same time.
As used herein, the term ‘rule’ signifies a process with at least one logical test (signified, e.g., by ‘IF test IS TRUE THEN DO process’). As used herein, a ‘grammar’ is a set of rules for determining the structure of information. Many forms of knowledge, learning, skills and styles are authored, structured, and enabled—objectively—as processes and/or rules—e.g., knowledge and learning as functions in knowledge programming languages.
As used herein, the term ‘component’ (also signified by ‘part’, and typically signified by ‘element’ when described in a patent text or diagram) signifies a physical object that is used to enable a process in combination with other components. For example, electronic components are used in processes that affect the physical state of one or more electromagnetic or quantum particles/waves (e.g., electrons, photons) or quasiparticles (e.g., electron holes, phonons, magnetic domains) and their associated fields or signals. Electronic components have at least two connection points which are attached to conductive components, typically a conductive wire or line, or an optical fiber, with one conductive component end attached to the component and the other end attached to another component, typically as part of a circuit with current or photon flows. There are at least three types of electrical components: passive, active and electromechanical. Passive electronic components typically do not introduce energy into a circuit—such components include resistors, memristors, capacitors, magnetic inductors, crystals, Josephson junctions, transducers, sensors, antennas, waveguides, etc. Active electronic components require a source of energy and can inject energy into a circuit—such components include semiconductors (e.g., diodes, transistors, optoelectronic devices), vacuum tubes, batteries, power supplies, displays (e.g., LEDs, LCDs, lamps, CRTs, plasma displays). Electromechanical components affect current flow using mechanical forces and structures—such components include switches, relays, protection devices (e.g., fuses, circuit breakers), heat sinks, fans, cables, wires, terminals, connectors and printed circuit boards.
As used herein, the term ‘netlist’ is a specification of components comprising an electric circuit, and electrical connections between the components. The programming language for the SPICE circuit simulation program is often used to specify a netlist. In the context of circuit design, the term ‘instance’ signifies each time a component is specified in a netlist.
One of the most important components as goods in commerce is the integrated circuit, and its res of abstractions. As used herein, the term ‘integrated circuit’ signifies a set of connected electronic components on a small substrate (thus the use of the signifier ‘chip’) of semiconductor material, such as silicon or gallium arsenide, with components fabricated on one or more layers. Other signifiers for ‘integrated circuit’ include ‘monolithic integrated circuit’, ‘IC’, ‘chip’, ‘microchip’ and ‘System on Chip’ (‘SoC’). Examples of types of integrated circuits include gate/logic arrays, processors, memories, interface chips, power controllers, and operational amplifiers. The term ‘cell’ as used in electronic circuit design signifies a specification of one or more components, for example, a set of transistors that are connected to function as a logic gate. Cells are usually stored in a database, to be accessed by circuit designers and design processes.
As used herein, the term ‘module’ signifies a tangible structure for acting on data and information. For example, the term ‘module’ can signify a process that transforms data and information, for example, a process comprising a computer program (defined below). The term ‘module’ also can signify one or more interconnected electronic components, such as digital logic devices. A process comprising a module, if specified in a programming language (defined below), such as System C or Verilog, also can be transformed into a specification for a structure of electronic components that transform data and information that produce the same result as the process. This last sentence follows from a modified Church-Turing thesis, which is simply expressed as “Whatever can be transformed by a (patentable) process and a processor, can be transformed by a (patentable) equivalent set of modules.”, as opposed to the doublethink of deleting only one of the “(patentable)”.
A module is permanently structured (e.g., circuits with unalterable connections), temporarily structured (e.g., circuits or processes that are alterable with sets of data), or a combination of the two forms of structuring. Permanently structured modules can be manufactured, for example, using Application Specific Integrated Circuits (‘ASICs’) such as Arithmetic Logic Units (‘ALUs’), Programmable Logic Arrays (‘PLAs’), or Read Only Memories (‘ROMs’), all of which are typically structured during manufacturing. For example, a permanently structured module can comprise an integrated circuit. Temporarily structured modules can be manufactured, for example, using Field Programmable Gate Arrays (FPGAs—for example, sold by Xilink or Intel's Altera), Random Access Memories (RAMs) or microprocessors. For example, data and information is transformed using data as an address in RAM or ROM memory that stores output data and information. One can embed temporarily structured modules in permanently structured modules (for example, a FPGA embedded into an ASIC).
Modules that are temporarily structured can be structured during multiple time periods. For example, a processor comprising one or more modules has its modules first structured by a manufacturer at a factory and then further structured by a user when used in commerce. The processor can comprise a set of one or more modules during a first time period, and then be restructured to comprise a different set of one or modules during a second time period. The decision to manufacture or implement a module in a permanently structured form, in a temporarily structured form, or in a combination of the two forms, depends on issues of commerce such as cost, time considerations, resource constraints, tariffs, maintenance needs, national intellectual property laws, and/or specific design goals [FACT]. How a module is used, its function, is mostly independent of the physical form in which it is manufactured or enabled. This last sentence also follows from the modified Church-Turing thesis.
As used herein, the term ‘processor’ signifies a tangible data and information processing machine for use in commerce that physically transforms, transfers, and/or transmits data and information, using at least one process. A processor consists of one or more modules, e.g., a central processing unit (‘CPU’) module; an input/output (‘I/O’) module, a memory control module, a network control module, and/or other modules. The term ‘processor’ can also signify one or more processors, or one or more processors with multiple computational cores/CPUs, specialized processors (for example, graphics processors or signal processors), and their combinations. Where two or more processors interact, one or more of the processors can be remotely located relative to the position of the other processors. Where the term ‘processor’ is used in another context, such as a ‘chemical processor’, it will be signified and defined in that context.
The processor can comprise, for example, digital logic circuitry (for example, a binary logic gate), and/or analog circuitry (for example, an operational amplifier). The processor also can use optical signal processing, DNA transformations, quantum operations, microfluidic logic processing, or a combination of technologies, such as an optoelectronic processor. For data and information structured with binary data, any processor that can transform data and information using the AND, OR and NOT logical operations (and their derivatives, such as the NAND, NOR, and XOR operations) also can transform data and information using any function of Boolean logic. A processor such as an analog processor, such as an artificial neural network, also can transform data and information. No scientific evidence exists that any of these technological processors are processing, storing and retrieving data and information, using any process or structure equivalent to the bioelectric structures and processes of the human brain.
The one or more processors also can use a process in a ‘cloud computing’ or ‘timesharing’ environment, where time and resources of multiple remote computers are shared by multiple users or processors communicating with the computers. For example, a group of processors can use at least one process available at a distributed or remote system, these processors using a communications network (e.g., the Internet, or an Ethernet) and using one or more specified network interfaces (‘interface’ defined below) (e.g., an application program interface (‘API’) that signifies functions and data structures to communicate with the remote process).
As used herein, the term ‘computer’ and ‘computer system’ (further defined below) includes at least one processor that, for example, performs operations on data and information such as (but not limited to) the Boolean logical operations using electronic gates that can comprise transistors, with the addition of memory (for example, memory structured with flip-flops using the NOT-AND or NOT-OR operation). Any processor that can perform the logical AND, OR and NOT operations (or their equivalent) is Turing-complete and computationally universal [FACT]. A computer can comprise a simple structure, for example, comprising an I/O module, a CPU module, and a memory that performs, for example, the process of inputting a signal, transforming the signal, and outputting the signal with no human intervention.
As used herein, the term ‘programming language’ signifies a structured grammar for specifying sets of operations and data for use by modules, processors and computers. Programming languages include assembler instructions, instruction-set-architecture instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more higher level languages, for example, the C programming language and similar general programming languages (such as Fortran, Basic, Javascript, PHP, Python, C++), knowledge programming languages (such as Lisp, Smalltalk, Prolog, or CycL), electronic structure programming languages (such as VHDL, Verilog, SPICE or SystemC), text programming languages (such as SGML, HTML, or XML), or audiovisual programming languages (such as SVG, MathML, X3D/VRML, or MIDI), and any future equivalent programming languages. As used herein, the term ‘source code’ signifies a set of instructions and data specified in text form using a programming language. A large amount of source code for use in enabling any of the claimed inventions is available on the Internet, such as from a source code library such as Github.
As used herein, the term ‘program’ (also referred to as an ‘application program’) signifies one or more processes and data structures that structure a module, processor or computer to be used as a “specific machine” (see In re Alappat, 33 F3d 1526 [CAFC, 1991]). One use of a program is to structure one or more computers, for example, standalone, client or server computers, or one or more modules, or systems of one or more such computers or modules. As used herein, the term ‘computer application’ signifies a program that enables a specific use, for example, to enable text processing operations, or to encrypt a set of data. As used herein, the term ‘firmware’ signifies a type of program that typically structures a processor or a computer, where the firmware is smaller in size than a typical application program, and is typically not very accessible to or modifiable by the user of a computer. Computer programs and firmware are often specified using source code written in a programming language, such as C. Modules, circuits, processors, programs and computers can be specified at multiple levels of abstraction, for example, using the SystemC programming language, and have value as products in commerce as taxable goods under the Uniform Commercial Code (see U.C.C. Article 2, Part 1).
A program is transferred into one or more memories of the computer or computer system from a data and information device or storage system. A computer system typically has a device for reading storage media that is used to transfer the program, and/or has an interface device that receives the program over a network. This transfer is discussed in the General Computer Explanation section.
In
The computer system can be structured as a server, a client, a workstation, a mainframe, a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a smartphone, a web appliance, a rack-mounted ‘blade’, a kiosk, a television, a game station, a network router, switch or bridge, or any data processing machine with instructions that specify actions to be taken by that machine. The term ‘server’, as used herein, refers to a computer or processor that typically performs processes for, and sends data and information to, another computer or processor.
A computer system typically is structured, in part, with at least one operating system program, such as Microsoft's Windows, Sun Microsystems's Solaris, Apple Computer's MacOs and iOS, Google's Android, Linux and/or Unix. The computer system typically includes a Basic Input/Output System (BIOS) and processor firmware. The operating system, BIOS and firmware are used by the processor to structure and control any subsystems and interfaces connected to the processor. Typical processors that enable these operating systems include: the Pentium, Itanium and Xeon processors from Intel; the Opteron and Athlon processors from Advanced Micro Devices; the Graviton processor from Amazon; the POWER processor from IBM; the SPARC processor from Oracle; and the ARM processor from ARM Holdings.
Any ECIN is limited neither to an electronic digital logic computer structured with programs nor to an electronically programmable device. For example, the claimed inventions can use an optical computer, a quantum computer, an analog computer, or the like. Further, where only a single computer system or a single machine is signified, the use of a singular form of such terms also can signify any structure of computer systems or machines that individually or jointly use processes. Due to the ever-changing nature of computers and networks, the description of computer system 510 depicted in
Network interface subsystem 516 provides an interface to outside networks, including an interface to communication network 518, and is coupled via communication network 518 to corresponding interface devices in other computer systems or machines. Communication network 518 can comprise many interconnected computer systems, machines and physical communication connections (signified by ‘links’). These communication links can be wireline links, optical links, wireless links (e.g., using the WiFi or Bluetooth protocols), or any other physical devices for communication of information. Communication network 518 can be any suitable computer network, for example a wide area network such as the Internet, and/or a local-to-wide area network such as Ethernet. The communication network is wired and/or wireless, and many communication networks use encryption and decryption processes, such as is available with a virtual private network. The communication network uses one or more communications interfaces, which receive data from, and transmit data to, other systems. Embodiments of communications interfaces typically include an Ethernet card, a modem (e.g., telephone, satellite, cable, or ISDN), (asynchronous) digital subscriber line (DSL) unit, Firewire interface, USB interface, and the like. Communication algorithms (‘protocols’) can be specified using one or communication languages, such as HTTP, TCP/IP, RTP/RTSP, IPX and/or UDP.
User interface input devices 522 can include an alphanumeric keyboard, a keypad, pointing devices such as a mouse, trackball, toggle switch, touchpad, stylus, a graphics tablet, an optical scanner such as a bar code reader, touchscreen electronics for a display device, audio input devices such as voice recognition systems or microphones, eye-gaze recognition, brainwave pattern recognition, optical character recognition systems, and other types of input devices. Such devices are connected by wire or wirelessly to a computer system. Typically, the term ‘input device’ signifies all possible types of devices and processes to transfer data and information into computer system 510 or onto communication network 518. User interface input devices typically enable a user to select objects, icons, text and the like that appear on some types of user interface output devices, for example, a display subsystem.
User interface output devices 520 can include a display subsystem, a printer, a fax machine, or a non-visual communication device such as audio and haptic devices. The display subsystem can include a cathode ray tube (CRT), a flat-panel device such as a liquid crystal display (LCD), an image projection device, or some other device for creating visible stimuli such as a virtual reality system. The display subsystem also can provide non-visual stimuli such as via audio output, aroma generation, or tactile/haptic output (e.g., vibrations and forces) devices. Typically, the term ‘output device’ signifies all possible types of devices and processes to transfer data and information out of computer system 510 to the user or to another machine or computer system. Such devices are connected by wire or wirelessly to a computer system. Note: some devices transfer data and information both into and out of the computer, for example, haptic devices that generate vibrations and forces on the hand of a user while also incorporating sensors to measure the location and movement of the hand. Technical applications of the sciences of ergonomics and semiotics are used to improve the efficiency of user interactions with any processes and computers disclosed herein, such as any interactions with regards to the design and manufacture of circuits, that use any of the above input or output devices.
Memory subsystem 526 typically includes a number of memories including a main random-access memory (‘RAM’) 530 (or other volatile storage device) for storage of instructions and data during program execution and a read only memory (‘ROM’) 532 in which fixed instructions are stored. File storage subsystem 528 provides persistent storage for program and data files, and can include a hard disk drive, a floppy disk drive along with associated removable media, a CD-ROM drive, an optical drive, a flash memory such as a USB drive, or removable media cartridges. If computer system 510 includes an input device that performs optical character recognition, then text and symbols printed on paper can be used as a device for storage of program and data files. The databases and modules used by some embodiments can be stored by file storage subsystem 528.
Bus subsystem 512 provides a device for transmitting data and information between the various components and subsystems of computer system 510. Although bus subsystem 512 is depicted as a single bus, alternative embodiments of the bus subsystem can use multiple busses. For example, a main memory using RAM can communicate directly with file storage systems using Direct Memory Access (‘DMA’) systems.
The signifier ‘commercial solution’ signifies, solely for the following paragraph, a technology domain-specific (and thus non-preemptive—see Bilski): electronic structure, process for a specified machine, manufacturable circuit (and its Church-Turing equivalents), or composition of matter that applies science and/or technology for use in commerce to solve an unmet need of technology.
The signifier ‘abstract’ (when used in a patent claim for any enabled embodiments disclosed herein for a new commercial solution that is a scientific use of one or more laws of nature {see Benson}, and that solves a problem of technology {see Diehr} for use in commerce-or improves upon an existing solution used in commerce {see Diehr})—is precisely defined by the inventor(s) {see MPEP 2111.01 (9th edition, Rev. 08.2017)} as follows:
The Detailed Description signifies in isolation the individual features, structures, functions, or characteristics described herein and any combination of two or more such features, structures, functions or characteristics, to the extent that such features, structures, functions or characteristics or combinations thereof are enabled by the Detailed Description as a whole in light of the knowledge and understanding of a skilled person, irrespective of whether such features, structures, functions or characteristics, or combinations thereof, solve any problems disclosed herein, and without limitation to the scope of the Claims of the patent. When an ECIN comprises a particular feature, structure, function or characteristic, it is within the knowledge and understanding of a skilled person to use such feature, structure, function, or characteristic in connection with another ECIN whether or not explicitly described, for example, as a substitute for another feature, structure, function or characteristic.
In view of the Detailed Description, a skilled person will understand that many variations of any ECIN can be enabled, such as function and structure of elements, described herein while being as useful as the ECIN. One or more elements of an ECIN can be substituted for one or more elements in another ECIN, as will be understood by a skilled person. Writings about any ECIN signify its use in commerce, thereby enabling other skilled people to similarly use this ECIN in commerce.
This Detailed Description is fitly written to provide knowledge and understanding. It is neither exhaustive nor limiting of the precise structures described, but is to be accorded the widest scope consistent with the disclosed principles and features. Without limitation, any and all equivalents described, signified or Incorporated By Reference (or explicitly incorporated) in this patent application are specifically incorporated into the Detailed Description. In addition, any and all variations described, signified or incorporated with respect to any one ECIN also can be included with any other ECIN. Any such variations include both currently known variations as well as future variations, for example any element used for enablement includes a future equivalent element that provides the same function, regardless of the structure of the future equivalent element.
It is intended that the domain of the set of claimed inventions and their embodiments be defined and judged by the following Claims and their equivalents. The Detailed Description includes the following Claims, with each Claim standing on its own as a separate claimed invention. Any ECIN can have more structure and features than are explicitly specified in the Claims.
This application is a continuation-in-part of, and claims the priority of, U.S. patent application Ser. No. 18/323,188, filed May 24, 2023, and entitled “CLOCK PERIOD SYNTHESIS,” which claims the benefit of priority to U.S. Provisional Application No. 63/502,567, filed May 16, 2023, and entitled “POWER MANAGEMENT OF POWER REGULATOR DURING HIGH CURRENT EVENTS,” the entirety of these applications are expressly incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 63502567 | May 2023 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 18323188 | May 2023 | US |
| Child | 18498810 | US |
