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In computer architecture, multithreading is the ability of a central processing unit (CPU) (or a single core in a multi-core processor) to provide multiple threads of execution concurrently, supported by the operating system. This approach differs from multiprocessing. In a multithreaded application, the threads share the resources of a single or multiple cores, which include the computing units, the CPU caches, and the translation lookaside buffer (TLB).
In computer engineering, computer architecture is a set of rules and methods that describe the functionality, organization, and implementation of computer systems. Some definitions of architecture define it as describing the capabilities and programming model of a computer but not a particular implementation. In other definitions computer architecture involves instruction set architecture design, microarchitecture design, logic design, and implementation.
A central processing unit (CPU), also called a central processor or main processor, is the electronic circuitry within a computer that carries out the instructions of a computer program by performing the basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions. The computer industry has used the term "central processing unit" at least since the early 1960s. Traditionally, the term "CPU" refers to a processor, more specifically to its processing unit and control unit (CU), distinguishing these core elements of a computer from external components such as main memory and I/O circuitry.
A multi-core processor is a single computing component with two or more independent processing units called cores, which read and execute program instructions. The instructions are ordinary CPU instructions but the single processor can run multiple instructions on separate cores at the same time, increasing overall speed for programs amenable to parallel computing. Manufacturers typically integrate the cores onto a single integrated circuit die or onto multiple dies in a single chip package. The microprocessors currently used in almost all personal computers are multi-core.
Where multiprocessing systems include multiple complete processing units in one or more cores, multithreading aims to increase utilization of a single core by using thread-level parallelism, as well as instruction-level parallelism. As the two techniques are complementary, they are sometimes combined in systems with multiple multithreading CPUs and with CPUs with multiple multithreading cores.
Instruction-level parallelism (ILP) is a measure of how many of the instructions in a computer program can be executed simultaneously.
The multithreading paradigm has become more popular as efforts to further exploit instruction-level parallelism have stalled since the late 1990s. This allowed the concept of throughput computing to re-emerge from the more specialized field of transaction processing. Even though it is very difficult to further speed up a single thread or single program, most computer systems are actually multitasking among multiple threads or programs. Thus, techniques that improve the throughput of all tasks result in overall performance gains.
In science and philosophy, a paradigm is a distinct set of concepts or thought patterns, including theories, research methods, postulates, and standards for what constitutes legitimate contributions to a field.
Transaction processing is information processing in computer science that is divided into individual, indivisible operations called transactions. Each transaction must succeed or fail as a complete unit; it can never be only partially complete.
Two major techniques for throughput computing are multithreading and multiprocessing .
Multiprocessing is the use of two or more central processing units (CPUs) within a single computer system. The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them. There are many variations on this basic theme, and the definition of multiprocessing can vary with context, mostly as a function of how CPUs are defined.
If a thread gets a lot of cache misses, the other threads can continue taking advantage of the unused computing resources, which may lead to faster overall execution, as these resources would have been idle if only a single thread were executed. Also, if a thread cannot use all the computing resources of the CPU (because instructions depend on each other's result), running another thread may prevent those resources from becoming idle.
Multiple threads can interfere with each other when sharing hardware resources such as caches or translation lookaside buffers (TLBs). As a result, execution times of a single thread are not improved and can be degraded, even when only one thread is executing, due to lower frequencies or additional pipeline stages that are necessary to accommodate thread-switching hardware.
A translation lookaside buffer (TLB) is a memory cache that is used to reduce the time taken to access a user memory location. It is a part of the chip’s memory-management unit (MMU). The TLB stores the recent translations of virtual memory to physical memory and can be called an address-translation cache. A TLB may reside between the CPU and the CPU cache, between CPU cache and the main memory or between the different levels of the multi-level cache. The majority of desktop, laptop, and server processors include one or more TLBs in the memory-management hardware, and it is nearly always present in any processor that utilizes paged or segmented virtual memory.
Overall efficiency varies; Intel claims up to 30% improvement with its Hyper-Threading Technology,while a synthetic program just performing a loop of non-optimized dependent floating-point operations actually gains a 100% speed improvement when run in parallel. On the other hand, hand-tuned assembly language programs using MMX or AltiVec extensions and performing data prefetches (as a good video encoder might) do not suffer from cache misses or idle computing resources. Such programs therefore do not benefit from hardware multithreading and can indeed see degraded performance due to contention for shared resources.
From the software standpoint, hardware support for multithreading is more visible to software, requiring more changes to both application programs and operating systems than multiprocessing. Hardware techniques used to support multithreading often parallel the software techniques used for computer multitasking. Thread scheduling is also a major problem in multithreading.
The simplest type of multithreading occurs when one thread runs until it is blocked by an event that normally would create a long-latency stall. Such a stall might be a cache miss that has to access off-chip memory, which might take hundreds of CPU cycles for the data to return. Instead of waiting for the stall to resolve, a threaded processor would switch execution to another thread that was ready to run. Only when the data for the previous thread had arrived, would the previous thread be placed back on the list of ready-to-run threads.
Conceptually, it is similar to cooperative multi-tasking used in real-time operating systems, in which tasks voluntarily give up execution time when they need to wait upon some type of the event. This type of multithreading is known as block, cooperative or coarse-grained multithreading.
The goal of multithreading hardware support is to allow quick switching between a blocked thread and another thread ready to run. To achieve this goal, the hardware cost is to replicate the program visible registers, as well as some processor control registers (such as the program counter). Switching from one thread to another thread means the hardware switches from using one register set to another; to switch efficiently between active threads, each active thread needs to have its own register set. For example, to quickly switch between two threads, the register hardware needs to be instantiated twice.
Additional hardware support for multithreading allows thread switching to be done in one CPU cycle, bringing performance improvements. Also, additional hardware allows each thread to behave as if it were executing alone and not sharing any hardware resources with other threads, minimizing the amount of software changes needed within the application and the operating system to support multithreading.
Many families of microcontrollers and embedded processors have multiple register banks to allow quick context switching for interrupts. Such schemes can be considered a type of block multithreading among the user program thread and the interrupt threads.[ citation needed ]
The purpose of interleaved multithreading is to remove all data dependency stalls from the execution pipeline. Since one thread is relatively independent from other threads, there is less chance of one instruction in one pipelining stage needing an output from an older instruction in the pipeline. Conceptually, it is similar to preemptive multitasking used in operating systems; an analogy would be that the time slice given to each active thread is one CPU cycle.
This type of multithreading was first called barrel processing, in which the staves of a barrel represent the pipeline stages and their executing threads. Interleaved, preemptive, fine-grained or time-sliced multithreading are more modern terminology.
In addition to the hardware costs discussed in the block type of multithreading, interleaved multithreading has an additional cost of each pipeline stage tracking the thread ID of the instruction it is processing. Also, since there are more threads being executed concurrently in the pipeline, shared resources such as caches and TLBs need to be larger to avoid thrashing between the different threads.
The most advanced type of multithreading applies to superscalar processors. Whereas a normal superscalar processor issues multiple instructions from a single thread every CPU cycle, in simultaneous multithreading (SMT) a superscalar processor can issue instructions from multiple threads every CPU cycle. Recognizing that any single thread has a limited amount of instruction-level parallelism, this type of multithreading tries to exploit parallelism available across multiple threads to decrease the waste associated with unused issue slots.
To distinguish the other types of multithreading from SMT, the term "temporal multithreading" is used to denote when instructions from only one thread can be issued at a time.
In addition to the hardware costs discussed for interleaved multithreading, SMT has the additional cost of each pipeline stage tracking the thread ID of each instruction being processed. Again, shared resources such as caches and TLBs have to be sized for the large number of active threads being processed.
Implementations include DEC (later Compaq) EV8 (not completed), Intel Hyper-Threading Technology, IBM POWER5, Sun Microsystems UltraSPARC T2, Cray XMT, and AMD Bulldozer and Zen microarchitectures.
A major area of research is the thread scheduler that must quickly choose from among the list of ready-to-run threads to execute next, as well as maintain the ready-to-run and stalled thread lists. An important subtopic is the different thread priority schemes that can be used by the scheduler. The thread scheduler might be implemented totally in software, totally in hardware, or as a hardware/software combination.
Another area of research is what type of events should cause a thread switch: cache misses, inter-thread communication, DMA completion, etc.
If the multithreading scheme replicates all of the software-visible state, including privileged control registers and TLBs, then it enables virtual machines to be created for each thread. This allows each thread to run its own operating system on the same processor. On the other hand, if only user-mode state is saved, then less hardware is required, which would allow more threads to be active at one time for the same die area or cost.
In computing, multitasking is the concurrent execution of multiple tasks over a certain period of time. New tasks can interrupt already started ones before they finish, instead of waiting for them to end. As a result, a computer executes segments of multiple tasks in an interleaved manner, while the tasks share common processing resources such as central processing units (CPUs) and main memory. Multitasking automatically interrupts the running program, saving its state and loading the saved state of another program and transferring control to it. This "context switch" may be initiated at fixed time intervals, or the running program may be coded to signal to the supervisory software when it can be interrupted.
In computing, a context switch is the process of storing the state of a process or of a thread, so that it can be restored and execution resumed from the same point later. This allows multiple processes to share a single CPU, and is an essential feature of a multitasking operating system.
In computing, a process is the instance of a computer program that is being executed by one or many threads. It contains the program code and its activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently.
In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. The implementation of threads and processes differs between operating systems, but in most cases a thread is a component of a process. Multiple threads can exist within one process, executing concurrently and sharing resources such as memory, while different processes do not share these resources. In particular, the threads of a process share its executable code and the values of its dynamically allocated variables and non-thread-local global variables at any given time.
Symmetric multiprocessing (SMP) involves a multiprocessor computer hardware and software architecture where two or more identical processors are connected to a single, shared main memory, have full access to all input and output devices, and are controlled by a single operating system instance that treats all processors equally, reserving none for special purposes. Most multiprocessor systems today use an SMP architecture. In the case of multi-core processors, the SMP architecture applies to the cores, treating them as separate processors.
A superscalar processor is a CPU that implements a form of parallelism called instruction-level parallelism within a single processor. In contrast to a scalar processor that can execute at most one single instruction per clock cycle, a superscalar processor can execute more than one instruction during a clock cycle by simultaneously dispatching multiple instructions to different execution units on the processor. It therefore allows for more throughput than would otherwise be not possible at a given clock rate. Each execution unit is not a separate processor, but an execution resource within a single CPU such as an arithmetic logic unit.
Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but it's gaining broader interest due to the physical constraints preventing frequency scaling. As power consumption by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.
Hyper-threading is Intel's proprietary simultaneous multithreading (SMT) implementation used to improve parallelization of computations performed on x86 microprocessors. It first appeared in February 2002 on Xeon server processors and in November 2002 on Pentium 4 desktop CPUs. Later, Intel included this technology in Itanium, Atom, and Core 'i' Series CPUs, among others.
Simultaneous multithreading (SMT) is a technique for improving the overall efficiency of superscalar CPUs with hardware multithreading. SMT permits multiple independent threads of execution to better utilize the resources provided by modern processor architectures.
Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance to describe a computing paradigm that researchers had been investigating since the early 1980s. This paradigm is also called Independence architectures. It was the basis for Intel and HP development of the Intel Itanium architecture, and HP later asserted that "EPIC" was merely an old term for the Itanium architecture. EPIC permits microprocessors to execute software instructions in parallel by using the compiler, rather than complex on-die circuitry, to control parallel instruction execution. This was intended to allow simple performance scaling without resorting to higher clock frequencies.
Temporal multithreading is one of the two main forms of multithreading that can be implemented on computer processor hardware, the other being simultaneous multithreading. The distinguishing difference between the two forms is the maximum number of concurrent threads that can execute in any given pipeline stage in a given cycle. In temporal multithreading the number is one, while in simultaneous multithreading the number is greater than one. Some authors use the term super-threading synonymously.
A barrel processor is a CPU that switches between threads of execution on every cycle. This CPU design technique is also known as "interleaved" or "fine-grained" temporal multithreading. Unlike simultaneous multithreading in modern superscalar architectures, it generally does not allow execution of multiple instructions in one cycle.
In computer engineering, microarchitecture, also called computer organization and sometimes abbreviated as µarch or uarch, is the way a given instruction set architecture (ISA) is implemented in a particular processor. A given ISA may be implemented with different microarchitectures; implementations may vary due to different goals of a given design or due to shifts in technology.
MAJC was a Sun Microsystems multi-core, multithreaded, very long instruction word (VLIW) microprocessor design from the mid-to-late 1990s. Originally called the UltraJava processor, the MAJC processor was targeted at running Java programs, whose "late compiling" allowed Sun to make several favourable design decisions. The processor was released into two commercial graphical cards from Sun. Lessons learned regarding multi-threads on a multi-core processor provided a basis for later OpenSPARC implementations such as the UltraSPARC T1.
Memory-level parallelism (MLP) is a term in computer architecture referring to the ability to have pending multiple memory operations, in particular cache misses or translation lookaside buffer (TLB) misses, at the same time.
Hardware scout is a technique that uses otherwise idle processor execution resources to perform prefetching during cache misses. When a thread is stalled by a cache miss, the processor pipeline checkpoints the register file, switches to runahead mode, and continues to issue instructions from the thread that is waiting for memory. The thread of execution in run-ahead mode is known as a scout thread. When the data returns from memory, the processor restores the register file contents from the checkpoint, and switches back to normal execution mode.
Latency oriented processor architecture is the microarchitecture of a microprocessor designed to serve a serial computing thread with a low latency. This is typical of most Central Processing Units (CPU) being developed since the 1970s. These architectures, in general, aim to execute as many instructions as possible belonging to a single serial thread, in a given window of time; however, the time to execute a single instruction completely from fetch to retire stages may vary from a few cycles to even a few hundred cycles in some cases. Latency oriented processor architectures are the opposite of throughput-oriented processors which concern themselves more with the total throughput of the system, rather than the service latencies for all individual threads that they work on.