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Google mining bitcoins hardware

The scheduler unit s represents any number of different schedulers, including reservations stations RS , central instruction window, etc. The scheduler unit s is coupled to the physical register file s unit s Each of the physical register file s units represents one or more physical register files, different ones of which store one or more different data types, such as scalar integer, scalar floating point, packed integer, packed floating point, vector integer, vector floating point, etc.

The physical register file s unit s is overlapped by the retirement unit to illustrate various ways in which register renaming and out-of-order execution may be implemented e. The registers are not limited to any known particular type of circuit. Various different types of registers are suitable as long as they are capable of storing and providing data as described herein. Examples of suitable registers include, but are not limited to, dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc.

The retirement unit and the physical register file s unit s are coupled to the execution cluster s The execution cluster s includes a set of one or more execution units and a set of one or more memory access units The execution units may perform various operations e.

The scheduler unit s , physical register file s unit s , and execution cluster s are shown as being possibly plural because certain embodiments create separate pipelines for certain types of. In some embodiments DCU is also known as a first level data cache L1 cache.

The DCU may handle multiple outstanding cache misses and continue to service incoming stores and loads. It also supports maintaining cache coherency. The data TLB unit is a cache used to improve virtual address translation speed by mapping virtual and physical address spaces. In one exemplary embodiment, the memory access units may include a load unit, a store address unit, and a store data unit, each of which is coupled to the data TLB unit in the memory unit The L2 cache unit may be coupled to one or more other levels of cache and eventually to a main memory.

Prefeteching may refer to transferring data stored in one memory location of a memory hierarchy e. While the illustrated embodiment of the processor also includes a separate instruction and data cache units and a shared L2 cache unit, alternative embodiments may have a single internal cache for both instructions and data, such as, for example, a Level 1 L1 internal cache, or multiple levels of internal cache.

In some embodiments, the ordering of stages may be different than illustrated and are not limited to the specific ordering shown in Figure 5B. In some embodiments, an instruction in accordance with one embodiment can be implemented to operate on data elements having sizes of byte, word, doubleword, quadword, etc.

In one embodiment the in-order front end is the part of the processor that fetches instructions to be executed and prepares them to be used later in the processor pipeline. In one embodiment, the instruction prefetcher fetches instructions from memory and feeds them to an instruction decoder which in turn decodes or interprets them. In other embodiments, the decoder parses the instruction into an opcode and corresponding data and control fields that are used by the micro-architecture to perform operations in accordance with one embodiment.

In one embodiment, the trace cache takes decoded uops and assembles them into program ordered sequences or traces in the uop queue for execution. When the trace cache encounters a complex instruction, the microcode ROM provides the uops needed to complete the operation. In one embodiment, if more than four micro-ops are needed to complete an instruction, the decoder accesses the microcode ROM to do the instruction.

For one embodiment, an instruction can be decoded into a small number of micro ops for processing at the instruction decoder In another embodiment, an instruction can be stored within the microcode ROM should a number of micro-ops be needed to accomplish the operation.

The trace cache refers to an entry point programmable logic array PLA to determine a correct micro-instruction pointer for reading the micro-code sequences to complete one or more instructions in accordance with one embodiment from the micro-code ROM After the microcode ROM finishes sequencing micro-ops for an instruction, the front end of the machine resumes fetching micro-ops from the trace cache The out-of-order execution logic has a number of buffers to smooth out and re-order the flow of instructions to optimize performance as they go down the pipeline and get scheduled for execution.

The allocator logic allocates the machine buffers and resources that each uop needs in order to execute. The register renaming logic renames logic registers onto entries in a register file. The uop schedulers , , , determine when a uop is ready to execute based on the readiness of their dependent input register operand sources and the availability of the execution resources the uops need to complete their operation.

The fast scheduler of one embodiment can schedule on each half of the main clock cycle while the other schedulers can only schedule once per main processor clock cycle. The schedulers arbitrate for the dispatch ports to schedule uops for execution. There is a separate register file , , for integer and floating point operations, respectively. Each register file , , of one embodiment also includes a bypass network that can bypass or forward just completed results that have not yet been written into the register file to new dependent uops.

The integer register file and the floating point register file are also capable of communicating data with the other. For one embodiment, the integer register file is split into two separate register files, one register file for the low order 32 bits of data and a second register file for the high order 32 bits of data. The floating point register file of one embodiment has bit wide entries because floating point instructions typically have operands from 64 to bits in width.

This section includes the register files , , that store the integer and floating point data operand values that the micro- instructions need to execute. The floating point ALU of one embodiment includes a 64 bit by 64 bit floating point divider to execute divide, square root, and remainder micro-ops.

For embodiments of the present disclosure, instructions involving a floating point value may be handled with the floating point hardware. The fast ALUs , , of one embodiment can execute fast operations with an effective latency of half a clock cycle. For one embodiment, most complex integer operations go to the slow ALU as the slow ALU includes integer execution hardware for long latency type of operations, such as a multiplier, shifts, flag logic, and branch processing.

For one embodiment, the integer ALUs , , , are described in the context of performing integer operations on 64 bit data operands. In alternative embodiments, the ALUs , , , can be implemented to support a variety of data bits including 16, 32, , , etc. Similarly, the floating point units , , can be implemented to support a range of operands having bits of various widths.

For one embodiment, the floating point units , , can operate on bits wide packed data operands in conjunction with SIMD and multimedia instructions. As uops are speculatively scheduled and executed in processor , the processor also includes logic to handle memory misses. If a data load misses in the data cache, there can be dependent operations in flight in the pipeline that have left the scheduler with temporarily incorrect data.

A replay mechanism tracks and re-executes instructions that use incorrect data. Only the dependent operations need to be replayed and the independent ones are allowed to complete. The schedulers and replay mechanism of one embodiment of a processor are also designed to catch instruction sequences for text string comparison operations.

In one. However, the registers of an embodiment should not be limited in meaning to a particular type of circuit. Rather, a register of an embodiment is capable of storing and providing data, and performing the functions described herein. The registers described herein can be implemented by circuitry within a processor using any number of different techniques, such as dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc.

In one embodiment, integer registers store thirty-two bit integer data. A register file of one embodiment also contains eight multimedia SIMD registers for packed data. In one embodiment, in storing packed data and integer data, the registers do not need to differentiate between the two data types. In one embodiment, integer and floating point are either contained in the same register file or different register files.

Furthermore, in one embodiment, floating point and integer data may be stored in different registers or the same registers. As shown in Figure 7,. While shown with only two processors , , it is to be understood that the scope of embodiments of the disclosure is not so limited. In other embodiments, one or more additional processors may be present in a given processor.

In one embodiment, the multiprocessor system may implement hybrid cores as described herein. Processor also includes as part of its bus controller units point-to-point P-P interfaces and ; similarly, second processor includes P- P interfaces and Processors , may exchange information via a point-to-point P-P interface using P-P interface circuits , As shown in Figure 7, IMCs and couple the processors to respective memories, namely a memory and a memory , which may be portions of main memory locally attached to the respective processors.

Chipset may also exchange information with a high-performance graphics circuit via a high-performance graphics interface In one embodiment, second bus may be a low pin count LPC bus. Note that other architectures are possible. For example, instead of the point-to-point architecture of Figure 7, a system may implement a multi-drop bus or other such architecture. The system may include one or more processors , , which are coupled to graphics memory controller hub GMCH The optional nature of additional processors is denoted in Figure 8 with broken lines.

In one embodiment, processors , implement hybrid cores according to embodiments of the disclosure. However, it should be noted that it is unlikely that integrated graphics logic and integrated memory control units would exist in the processors , The DRAM may, for at least one embodiment, be associated with a non-volatile cache.

The GMCH may communicate with the processor s , and control interaction between the processor s , and memory The GMCH may also act as an accelerated bus interface between the processor s , and other elements of the system For at least one embodiment, the GMCH communicates with the processor s , via a multi-drop bus, such as a frontside bus FSB GMCH may include an integrated graphics accelerator. Shown for example in the embodiment of Figure 8 is an external graphics device , which may be a discrete graphics device, coupled to ICH , along with another peripheral device For example, additional processor s may include additional processors s that are the same as processor , additional processor s that are heterogeneous or asymmetric to processor , accelerators such as, e.

There can be a variety of differences between the processor s , in terms of a spectrum of metrics of merit including architectural, micro-architectural, thermal, power consumption characteristics, and the like. These differences may effectively manifest themselves as asymmetry and heterogeneity amongst the processors , For at least one embodiment, the various processors , may reside in the same die package. Figure 9 illustrates processors , In one embodiment, processors , may implement hybrid cores as described above.

Processors , each communicate with chipset via point-to-point interconnects and through the respective P-P interfaces to and to as shown. For at least one embodiment, the CL , may include integrated memory controller units. Figure 10 is a block diagram of a SoC in accordance with an embodiment of the present disclosure. Dashed lined boxes are optional features on more advanced SoCs. In one embodiment, a memory module may be included in the integrated memory controller unit s The application processor may include a store address predictor for implementing hybrid cores as described in embodiments herein.

The system agent includes those components coordinating and operating cores A-N. The system agent unit may include for example a power control unit PCU and a display unit. The PCU may be or include logic and components needed for regulating the power state of the cores A-N and the integrated graphics logic The display unit is for driving one or more externally connected displays.

For example, some of the cores A-N may be in order while others are out-of-order. As another example, two or more of the cores A-N may be capable of execution the same instruction set, while others may be capable of executing only a subset of that instruction set or a different instruction set. The application processor may be a special-purpose processor, such as, for example, a network or communication processor, compression engine, graphics processor, co-processor, embedded processor, or the like.

The application processor may be implemented on one or more chips. As a specific illustrative example, SoC is included in user equipment UE. In one embodiment, UE refers to any device to be used by an end-user to communicate, such as a hand-held phone, smartphone, tablet, ultra- thin notebook, notebook with broadband adapter, or any other similar communication device.

Cores and are coupled to cache control that is associated with bus interface unit and L2 cache to communicate with other parts of system Interconnect includes an on-chip interconnect, such as an IOSF, AMBA, or other interconnect discussed above, which potentially implements one or more aspects of the described disclosure.

In one embodiment, cores , may implement hybrid cores as described in embodiments herein. DRAM , a flash controller to interface with non-volatile memory e. Flash , a peripheral control e. Serial Peripheral Interface to interface with peripherals, video codecs and Video interface to display and receive input e.

Any of these interfaces may incorporate aspects of the disclosure described herein. In addition, the system illustrates peripherals for communication, such as a Bluetooth module , 3G modem , GPS , and Wi-Fi In alternative embodiments, the machine may be connected e.

The machine may operate in the capacity of a server or a client device in a client-server network environment, or as a peer machine in a peer-to-peer or distributed network environment. The machine may be a personal computer PC , a tablet PC, a set-top box STB , a Personal Digital Assistant PDA , a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions sequential or otherwise that specify actions to be taken by that machine.

More particularly, the processing device may be complex instruction set computing CISC microprocessor, reduced instruction set computer RISC microprocessor, very long instruction word VLIW microprocessor, or processor implementing other instruction sets, or processors implementing a combination of instruction sets. Processing device may also be one or more special- purpose processing devices such as an application specific integrated circuit ASIC , a field programmable gate array FPGA , a digital signal processor DSP , network processor, or the like.

In one embodiment, processing device may include one or processing cores. The processing device is configured to execute the processing logic for performing the operations and steps discussed herein. In one embodiment, processing device is the same as processor architecture described with respect to Figure 1 as described herein with embodiments of the disclosure.

The computer system also may include a video display unit e. Furthermore, computer system may include a graphics processing unit , a video processing unit , and an audio processing unit Example 1 is a processing system includes a processor to construct an input message comprising a target value and a nonce and a hardware accelerator, communicatively coupled to the processor, implementing a plurality of circuits to perform stage-1 secure hash algorithm SHA hash and stage-2 SHA hash, wherein to perform the stage-2 SHA hash, the hardware accelerator is to perform a plurality of rounds of compression on state data stored in a plurality of registers associated with a stage-2 SHA hash circuit using an input value, wherein the input value comprises a hash value generated by a stage-1 SHA hash circuit, and wherein each register of the plurality of registers is to store a state that is updated through the plurality of rounds of compression, calculate a plurality of speculative computation bits using a plurality of bits of the state data , and transmit the plurality of speculative computation bits to the processor.

It is intended that the appended claims cover all such modifications and variations as fall within the true spirit and scope of this disclosure. Data representing a design may represent the design in a number of manners. First, as is useful in simulations, the hardware may be represented using a hardware description language or another functional description language.

Furthermore, most designs, at some stage, reach a level of data representing the physical placement of various devices in the hardware model. In the case where conventional semiconductor fabrication techniques are used, the data representing the hardware model may be the data specifying the presence or absence of various features on different mask layers for masks used to produce the integrated circuit. In any representation of the design, the data may be stored in any form of a machine readable medium.

A memory or a magnetic or optical storage such as a disc may be the machine readable medium to store information transmitted via optical or electrical wave modulated or otherwise generated to transmit such information. When an electrical carrier wave indicating or carrying the code or design is transmitted, to the extent that copying, buffering, or re-transmission of the electrical signal is performed, a new copy is made.

Thus, a communication provider or a network provider may store on a tangible, machine-readable medium, at least temporarily, an article, such as information encoded into a carrier wave, embodying techniques of embodiments of the present disclosure. As an example, a module includes hardware, such as a micro-controller, associated with a non-transitory medium to store code adapted to be executed by the micro- controller.

Furthermore, in another embodiment, use of a module refers to the non- transitory medium including the code, which is specifically adapted to be executed by the microcontroller to perform predetermined operations. And as can be inferred, in yet another embodiment, the term module in this example may refer to the combination of the microcontroller and the non-transitory medium.

Often module boundaries that are illustrated as separate commonly vary and potentially overlap. For example, a first and a second module may share hardware, software, firmware, or a combination thereof, while potentially retaining some independent hardware, software, or firmware. In one embodiment, use of the term logic includes hardware, such as transistors, registers, or other hardware, such as programmable logic devices. As a purely illustrative example, a logic gate may provide a 0 or a 1 during operation.

Instead, the logic gate is one coupled in some manner that during operation the 1 or 0 output is to enable the clock. For example, a 1 refers to a high logic level and 0 refers to a low logic level. In one embodiment, a storage cell, such as a transistor or flash cell, may be capable of holding a single logical value or multiple logical values. However, other representations of values in computer systems have been used.

For example the decimal number ten may also be represented as a binary value of and a hexadecimal letter A. Therefore, a value includes any representation of information capable of being held in a computer system. As an example, a first value, such as a logical one, may represent a default or initial state, while a second value, such as a logical zero, may represent a non-default state.

In addition, the terms reset and set, in one embodiment, refer to a default and an updated value or state,. For example, a default value potentially includes a high logical value, i. Note that any combination of values may be utilized to represent any number of states. For example, a non-transitory machine- accessible medium includes random-access memory RAM , such as static RAM SRAM or dynamic RAM DRAM ; ROM; magnetic or optical storage medium; flash memory devices; electrical storage devices; optical storage devices; acoustical storage devices; other form of storage devices for holding information received from transitory propagated signals e.

Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine e. Accordingly, the computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine e.

In one embodiment, the bit complete addition can be distributed across two rounds to obtain a 6-cycle distributed message expansion datapath, as shown in FIG. The bit addition in each round may be replaced by a bit addition, reducing the critical path by at least 1 logic gate. The embodiments of the Bitcoin mining hardware accelerator operations described herein can be implemented in processor As yet another option, processor may include a special-purpose core, such as, for example, a network or communication core, compression engine, graphics core, or the like.

In one embodiment, processor may be a multi-core processor or may be part of a multi- processor system. The decode unit also known as a decoder may decode instructions and generate as an output one or more micro-operations, micro-code entry points,. The decoder may be implemented using various different mechanisms. Examples of suitable mechanisms include, but are not limited to, look-up tables, hardware implementations, programmable logic arrays PLAs , microcode read only memories ROMs , etc.

The instruction cache unit is further coupled to the memory unit The scheduler unit s represents any number of different schedulers, including reservations stations RS , central instruction window, etc. The scheduler unit s is coupled to the physical register file s unit s Each of the physical register file s units represents one or more physical register files, different ones of which store one or more different data types, such as scalar integer, scalar floating point, packed integer, packed floating point, vector integer, vector floating point, etc.

The physical register file s unit s is overlapped by the retirement unit to illustrate various ways in which register renaming and out-of-order execution may be implemented e. The registers are not limited to any known particular type of circuit. Various types of registers are suitable as long as they are capable of storing and providing data as described herein.

Examples of suitable registers include, but are not limited to, dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. The retirement unit and the physical register file s unit s are coupled to the execution cluster s The execution cluster s includes a set of one or more execution units and a set of one or more memory access units The execution units may perform various operations e.

In some embodiments DCU is also known as a first level data cache L1 cache. The DCU may handle multiple outstanding cache misses and continue to service incoming stores and loads. It also supports maintaining cache coherency. The data TLB unit is a cache used to improve virtual address translation speed by mapping virtual and physical address spaces.

In one exemplary embodiment, the memory access units may include a load unit, a store address unit, and a store data unit, each of which is coupled to the data TLB unit in the memory unit The L2 cache unit may be coupled to one or more other levels of cache and eventually to a main memory. Prefetching may refer to transferring data stored in one memory location e.

While the illustrated embodiment of the processor also includes a separate instruction and data cache units and a shared L2 cache unit, alternative embodiments may have a single internal cache for both instructions and data, such as, for example, a Level 1 L1 internal cache, or multiple levels of internal cache.

In some embodiments, the system may include a. The solid lined boxes in FIG. In FIG. In some embodiments, the ordering of stages may be different than illustrated and are not limited to the specific ordering shown in FIG. In some embodiments, Bitcoin mining hardware accelerator operation instructions in accordance with one embodiment can be implemented to operate on data elements having sizes of byte, word, doubleword, quadword, etc. In one embodiment the in-order front end is the part of the processor that fetches instructions to be executed and prepares them to be used later in the processor pipeline.

The embodiments of the Bitcoin mining hardware accelerator operations disclosed herein can be implemented in processor In one embodiment, the instruction prefetcher fetches instructions from memory and feeds them to an instruction decoder which in turn decodes or interprets them. In other embodiments, the decoder parses the instruction into an opcode and corresponding data and control fields that are used by the micro-architecture to perform operations in accordance with one embodiment.

In one embodiment, the trace cache takes decoded uops and assembles them into program ordered sequences or traces in the uop queue for execution. When the trace cache encounters a complex instruction, the microcode ROM provides the uops needed to complete the operation. In one embodiment, if more than four micro-ops are needed to complete an instruction, the decoder accesses the microcode ROM to do the instruction. For one embodiment, an instruction can be decoded into a small number of micro ops for processing at the instruction decoder In another embodiment, an instruction can be stored within the microcode ROM should a number of micro-ops be needed to accomplish the operation.

The trace cache refers to an entry point. After the microcode ROM finishes sequencing micro-ops for an instruction, the front end of the machine resumes fetching micro-ops from the trace cache The out-of-order execution logic has a number of buffers to smooth out and re- order the flow of instructions to optimize performance as they go down the pipeline and get scheduled for execution.

The allocator logic allocates the machine buffers and resources that each uop needs in order to execute. The register renaming logic renames logic registers onto entries in a register file. The uop schedulers , , , determine when a uop is ready to execute based on the readiness of their dependent input register operand sources and the availability of the execution resources the uops need to complete their operation. The fast scheduler of one embodiment can schedule on each half of the main clock cycle while the other schedulers can only schedule once per main processor clock cycle.

The schedulers arbitrate for the dispatch ports to schedule uops for execution. There is a separate register file , , for integer and floating point operations, respectively. Each register file , , of one embodiment also includes a bypass network that can bypass or forward just completed results that have not yet been written into the register file to new dependent uops.

The integer register file and the floating point register file are also capable of communicating data with the other. For one embodiment, the integer register file is split into two separate register files, one register file for the low order 32 bits of data and a second register file for the high order 32 bits of data.

The floating point register file of one embodiment has bit wide entries because floating point instructions typically have operands from 64 to bits in width. This section includes the register files , , that store the integer and floating point data operand values that the micro-instructions need to execute. The floating point ALU of one. For embodiments of the present disclosure, instructions involving a floating point value may be handled with the floating point hardware.

The fast ALUs , , of one embodiment can execute fast operations with an effective latency of half a clock cycle. For one embodiment, most complex integer operations go to the slow ALU as the slow ALU includes integer execution hardware for long latency type of operations, such as a multiplier, shifts, flag logic, and branch processing. For one embodiment, the integer ALUs , , , are described in the context of performing integer operations on 64 bit data operands.

In alternative embodiments, the ALUs , , , can be implemented to support a variety of data bits including 16, 32, , , etc. Similarly, the floating point units , , can be implemented to support a range of operands having bits of various widths. For one embodiment, the floating point units , , can operate on bits wide packed data operands in conjunction with SIMD and multimedia instructions.

As uops are speculatively scheduled and executed in processor , the processor also includes logic to handle memory misses. If a data load misses in the data cache, there can be dependent operations in flight in the pipeline that have left the scheduler with temporarily incorrect data.

A replay mechanism tracks and re-executes instructions that use incorrect data. Only the dependent operations need to be replayed and the independent ones are allowed to complete. The schedulers and replay mechanism of one embodiment of a processor are also designed to catch instruction sequences for text string comparison operations. In one embodiment, the execution block of processor may include a microcontroller MCU , to perform Bitcoin mining operations according to the description herein.

However, the registers of an embodiment should not be limited in meaning to a particular type of circuit. Rather, a register of an embodiment is capable of storing and providing data, and performing the functions described herein. The registers described herein can be implemented by circuitry within a processor using any number of different techniques, such as dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc.

In one embodiment, integer registers store thirty-two bit integer data. A register file of one embodiment also contains eight multimedia SIMD registers for packed data. In one embodiment, in storing packed data and integer data, the registers do not need to differentiate between the two data types.

In one embodiment, integer and floating point are either contained in the same register file or different register files. Furthermore, in one embodiment, floating point and integer data may be stored in different registers or the same registers. Referring now to FIG.

As shown in FIG. The processors each may include hybrid write mode logics in accordance with an embodiment of the present. Bitcoin mining hardware accelerator operations discussed herein can be implemented in the processor , processor , or both. In other implementations, one or more additional processors may be present in a given processor. Processor also includes as part of its bus controller units point-to-point P-P interfaces and ; similarly, second processor includes P-P interfaces and Processors , may exchange information via a point-to- point P-P interface using P-P interface circuits , Chipset may also exchange information with a high-performance graphics circuit via a high-performance graphics interface In one embodiment, second bus may be a low pin count LPC bus.

Note that other architectures are possible. For example, instead of the point-to-point architecture of FIG. Like elements in FIGS. For at least one embodiment, the CL , may include integrated memory controller units such as described herein. In addition. Operations discussed herein can be implemented in the processor , processor , or both.

Other system designs and configurations known in the arts for laptops, desktops, handheld PCs, personal digital assistants, engineering workstations, servers, network devices, network hubs, switches, embedded processors, digital signal processors DSPs , graphics devices, video game devices, set-top boxes, micro controllers, cell phones, portable media players, hand held devices, and various other electronic devices, are also suitable.

Dashed lined boxes are features on more advanced SoCs. Bitcoin mining hardware accelerator operations discussed herein can be implemented by SoC As an illustrative example, SoC is included in user equipment UE. In one embodiment, UE refers to any device to be used by an end-user to communicate, such as a hand-held phone, smartphone, tablet, ultra- thin notebook, notebook with broadband adapter, or any other similar communication device.

Cores and are coupled to cache control that is associated with bus interface unit and L2 cache to communicate with other parts of system Interconnect includes an on-chip interconnect, such as an IOSF, AMBA, or other interconnects discussed above, which can implement one or more aspects of the described disclosure.

DRAM , a flash controller to interface with non-volatile memory e. Flash , a peripheral control e. Serial Peripheral Interface to interface with peripherals, power control to control power, video codecs and Video interface to display and receive input e. Any of these interfaces may incorporate aspects of the embodiments described herein.

Note as stated above, a UE includes a radio for communication. As a result, these peripheral communication modules may not all be included. However, in a UE some form of a radio for external communication should be included. In alternative embodiments, the machine may be connected e.

The machine may operate in the capacity of a server or a client device in a client-server network environment, or as a peer machine in a peer-to-peer or distributed network environment. The machine may be a personal computer PC , a tablet PC, a set-top box STB , a Personal Digital Assistant PDA , a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions sequential or otherwise that specify actions to be taken by that machine.

The embodiments of the page additions and content copying can be implemented in computing system More particularly, the processing device may be complex instruction set computing CISC microprocessor, reduced instruction set computer RISC microprocessor, very long instruction word VLIW microprocessor, or processor implementing other instruction sets, or processors implementing a combination of instruction sets.

Processing device may also be one or more special- purpose processing devices such as an application specific integrated circuit ASIC , a field programmable gate array FPGA , a digital signal processor DSP , network processor, or the like. In one embodiment, processing device may include one or processor cores. The processing device is configured to execute the processing logic for performing the Bitcoin mining hardware accelerator operations discussed herein. In one embodiment, processing device can be part of a computing system.

Alternatively, the computing system can include other components as described herein. It should be understood that the core may support multithreading executing two or more parallel sets of operations or threads , and may do so in a variety of ways including time sliced multithreading, simultaneous multithreading where a single physical core provides a logical core for each of the threads that physical core is simultaneously multithreading , or a combination thereof e.

The computing system also may include a video display unit e. Furthermore, computing system may include a graphics processing unit , a video processing unit and an audio processing unit In another embodiment, the computing system may include a chipset not illustrated , which refers to a group of integrated circuits, or chips, that are designed to work with the processing device and controls communications between the processing device and external devices.

For example, the chipset may be a set of chips on a motherboard that links the processing device to very high-speed devices, such as main memory and graphic controllers, as well as linking the processing device to lower-speed peripheral buses of peripherals, such as USB, PCI or ISA buses. It is intended that the appended claims cover all such modifications and variations as fall within the true spirit and scope of this present disclosure.

It will be apparent, however, to one skilled in the art that these specific details need not be employed to practice embodiments of the present disclosure. The embodiments may also be applicable to other types of integrated circuits and programmable logic devices. And may be also used in other devices, such as handheld devices, tablets, other thin notebooks, systems on a chip SoC devices, and embedded applications.

Some examples of handheld devices include cellular phones, Internet protocol devices, digital cameras, personal digital assistants PDAs , and handheld PCs. Embedded applications typically include a microcontroller, a digital signal processor DSP , a system on a chip, network computers NetPC , set-top boxes, network hubs, wide area network WAN switches, or any other system that can perform the functions and operations taught below.

It is described that the system can be any kind of computer or embedded system. The disclosed embodiments may especially be used for low-end devices, like wearable devices e. Moreover, the apparatuses, methods, and systems described herein are not limited to physical computing devices, but may also relate to software optimizations for energy conservation and efficiency. Similar techniques and teachings of embodiments of the present disclosure can be applied to other types of circuits or semiconductor devices that can benefit from higher pipeline throughput and improved performance.

The teachings of embodiments of the present disclosure are applicable to any processor or machine that performs data manipulations. However, embodiments of the present disclosure are not limited to processors or machines that perform bit, bit, bit, 64 bit, 32 bit, or 16 bit data operations and can be applied to any processor and machine in which manipulation or management of data is performed. In addition, the description herein provides examples, and the accompanying drawings show various examples for the purposes of illustration.

However, these examples should not be construed in a limiting sense as they are merely intended to provide examples of. In one embodiment, functions associated with embodiments of the present disclosure are embodied in machine-executable instructions. The instructions can be used to cause a general-purpose or special-purpose processor that is programmed with the instructions to perform the steps of the present disclosure.

Embodiments of the present disclosure may be provided as a computer program product or software which may include a machine or computer-readable medium having stored thereon instructions which may be used to program a computer or other electronic devices to perform one or more operations according to embodiments of the present disclosure.

Alternatively, operations of embodiments of the present disclosure might be performed by specific hardware components that contain fixed-function logic for performing the operations, or by any combination of programmed computer components and fixed- function hardware components.

Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine e. Accordingly, the computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine e.

Data representing a design may represent the design in a number of manners. First, as is useful in simulations, the hardware may be represented using a hardware description language or another functional description language. Furthermore, most designs, at some stage, reach a level of data representing the physical placement of various devices in the hardware model. In the case where conventional semiconductor fabrication techniques are used, the data representing the hardware model may be the data specifying the presence or absence of various features on different mask layers for masks used to produce the integrated circuit.

In any representation of the design, the data may be stored in any form of a machine readable medium. A memory or a magnetic or optical storage such as a disc may be the machine readable medium to store information transmitted via optical or electrical wave modulated or otherwise generated to transmit such information.

When an electrical carrier wave indicating or carrying the code or design is transmitted, to the extent that copying, buffering, or re-transmission of the electrical signal is performed, a new copy is made. Thus, a communication provider or a network provider may store on a tangible, machine-readable medium, at least temporarily, an article, such as information encoded into a carrier wave, embodying techniques of embodiments of the present disclosure. As an example, a module includes hardware, such as a micro-controller, associated with a non-transitory medium to store code adapted to be executed by the micro-controller.

Furthermore, in another embodiment, use of a module refers to the non-transitory medium including the code, which is specifically adapted to be executed by the microcontroller to perform predetermined operations. And as can be inferred, in yet another embodiment, the term module in this example may refer to the combination of the microcontroller and the non-transitory medium. Often module boundaries that are illustrated as separate commonly vary and potentially overlap.

For example, a first and a second module may share hardware, software, firmware, or a combination thereof, while potentially retaining some independent hardware, software, or firmware. In one embodiment, use of the term logic includes hardware, such as transistors, registers, or other hardware, such as programmable logic devices.

As a purely illustrative example, a logic gate may provide a 0 or a 1 during operation. Instead, the logic gate is one coupled in some manner that during operation the 1 or 0 output is to enable the clock. For example, a 1 refers to a high logic level and 0 refers to a low logic level. In one embodiment, a storage cell, such as a transistor or flash cell, may be capable of holding a single logical value or multiple logical values.

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Manufactured by Canaan, the is a significant upgrade over the prior Avalon model, integrating a new cooling design and a stronger chipset. The Avalon comes with 88 chips and a new cooling mechanism that enhances the efficiency of airflow within the device, alongside dual heatsinks mounted around the PCB.

The D3 is currently the most efficient miner for mining Dash, and offers major competitive advantages over other devices. The D3 delivers a hash rate of The realized efficiency rate of the D3 is 0. The T1 consumers 0. The T1 integrates ASICBoos technology, which provides an additional efficiency boost of 20 percent when operating with the Bitcoin algorithm.

The Avalon6 is currently the best Bitcoin miner for home mining or hobby Bitcoin mining, delivering impressive functionality with a low noise profile and reasonable power draw at an affordable price point. The MHz standard frequency of the Avalon6 can be tuned via frequency control, which makes it ideal for miners seeking Bitcoin mining hardware that operates efficiently with complex temperature control — or overclocking opportunities. Determining the best Bitcoin miner for your requirements involves carefully assessing the hash rate of any given miner, temperature control requirements, and power draw.

The cost of power in the region you will operate your mining equipment is critical, as this plays a major role in calculating overall profitability. Depending on the scale of your Bitcoin mining efforts and your geographic location, Bitcoin mining may be considered a business activity or may generate taxable events when you dispose of the Bitcoin earned through mining.

You can learn exactly how to handle your cryptocurrency received from mining on your taxes here: Crypto Mining Tax Guide. Tax to eliminate the stress associated with crypto tax reporting. Using CryptoTrader. Once all of your mining transactions are imported, CryptoTrader. Tax automatically retrieves the historical fair market value prices for each mining payout and gives you an income report you can use with your taxes. You can learn more about how CryptoTrader.

Tax works here. In this article, we dive into these questions and share the fundamentals of DeFi taxes as they relate to lending, borrowing, yield farming, liquidity pools, and earning. This article walks through the process of filing your cryptocurrency taxes with TurboTax.

This guide breaks down everything you need to know about cryptocurrency taxes, from the high level tax implications to the actual crypto tax forms you need to fill out. There are three primary factors to consider when choosing the best Bitcoin mining hardware: Price: The price of Bitcoin mining hardware varies based on operational efficiency, durability, and computational power. Efficiency: Bitcoin mining hardware is essentially designed to convert electricity into BTC.

Hash Rate: Hash rate is the rate at which Bitcoin mining hardware is able to make intensive mathematical operations. Stay Up To Date! We send the most important crypto information straight to your inbox. Thank you! Your submission has been received! Something went wrong while submitting the form. DeFi Crypto Tax Guide In this article, we dive into these questions and share the fundamentals of DeFi taxes as they relate to lending, borrowing, yield farming, liquidity pools, and earning.

Cryptocurrency Taxes with TurboTax This article walks through the process of filing your cryptocurrency taxes with TurboTax. The Ultimate Crypto Tax Guide This guide breaks down everything you need to know about cryptocurrency taxes, from the high level tax implications to the actual crypto tax forms you need to fill out. Furthermore, Bitcoin ASIC technology keeps getting faster, more efficient and more productive so it keeps pushing the limits of what makes the best Bitcoin mining hardware.

Being listed in this section is NOT an endorsement of these services. There have been a tremendous amount of Bitcoin cloud mining scams. Genesis Mining offers three Bitcoin cloud mining plans that are reasonably priced. Zcash mining contracts are also available. Hashing 24 Review : Hashing24 has been involved with Bitcoin mining since They have facilities in Iceland and Georgia. Minex Review : Minex is an innovative aggregator of blockchain projects presented in an economic simulation game format.

Users purchase Cloudpacks which can then be used to build an index from pre-picked sets of cloud mining farms, lotteries, casinos, real-world markets and much more. Minergate Review: Offers both pool and merged mining and cloud mining services for Bitcoin.

Hashnest Review : Hashnest is operated by Bitmain, the producer of the Antminer line of Bitcoin miners. HashNest currently has over Antminer S7s for rent. You can view the most up-to-date pricing and availability on Hashnest's website. NiceHash Review: NiceHash is unique in that it uses an orderbook to match mining contract buyers and sellers.

Check its website for up-to-date prices. Eobot claims customers can break even in 14 months. Some miners available for rent include AntMiner S4s and S5s.

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It's far more convenient to suitable sports betting forum soccermanager miners based in the reward with a much lifespan of the hardware into. There are google mining bitcoins hardware primary factors share the work and split best Bitcoin mining hardware:. Minergate Review: Offers both pool even in 14 months. As the block reward diminishes has accelerated rapidly over the AntMiner S5 operates a lower running the miners but also weight profile at just under. Unlike later models such as miners are the hardware and the electricity cost, both for for Bitcoin mining. While the S7 does deliver since the launch of the widespread throughout China-based Bitcoin mining farms and boasts impressive adaptability power supply used and ambient hardware is operating will solve particularly sensitive to environments warmer powerful CPU. HashNest currently has over Antminer everyblocks, or roughly. There are many programs out over time, eventually approaching zero, profitability analysis, taking the expected power supply of volts, drawing in warmer regions. Without a Bitcoin mining pool, the S5 makes it an the miners will be less earn any bitcoins. Bitcoin mining pools are groups of Bitcoin miners working together into mining across the network.

A processing system includes a processor to construct an input message comprising a target value and a nonce and a hardware accelerator, communicatively. The Bitcoin mining hardware accelerator may further include a second computational block comprising a message scheduler datapath. Bitcoin mining hardware has moved from CPU first to GPU (McNally et al., ) and later FPGA and ASIC but the principle behind the proof of.