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A superscalar processor (or multiple-issue processor [1] ) is a CPU that implements a form of parallelism called instruction-level parallelism within a single processor. [2] In contrast to a scalar processor, which 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 more throughput (the number of instructions that can be executed in a unit of time) than would otherwise be possible at a given clock rate. Each execution unit is not a separate processor (or a core if the processor is a multi-core processor), but an execution resource within a single CPU such as an arithmetic logic unit.
While a superscalar CPU is typically also pipelined, superscalar and pipelining execution are considered different performance enhancement techniques. The former (superscalar) executes multiple instructions in parallel by using multiple execution units, whereas the latter (pipeline) executes multiple instructions in the same execution unit in parallel by dividing the execution unit into different phases. In the "Simple superscalar pipeline" figure, fetching two instructions at the same time is superscaling, and fetching the next two before the first pair has been written back is pipelining.
The superscalar technique is traditionally associated with several identifying characteristics (within a given CPU):
Seymour Cray's CDC 6600 from 1964 is often mentioned as the first superscalar design. The 1967 IBM System/360 Model 91 was another superscalar mainframe. The Intel i960CA (1989), [3] the AMD 29000-series 29050 (1990), and the Motorola MC88110 (1991), [4] microprocessors were the first commercial single-chip superscalar microprocessors. RISC microprocessors like these were the first to have superscalar execution, because RISC architectures free transistors and die area which can be used to include multiple execution units and the traditional uniformity of the instruction set favors superscalar dispatch (this was why RISC designs were faster than CISC designs through the 1980s and into the 1990s, and it's far more complicated to do multiple dispatch when instructions have variable bit length).
Except for CPUs used in low-power applications, embedded systems, and battery-powered devices, essentially all general-purpose CPUs developed since about 1998 are superscalar.
The P5 Pentium was the first superscalar x86 processor; the Nx586, P6 Pentium Pro and AMD K5 were among the first designs which decode x86-instructions asynchronously into dynamic microcode-like micro-op sequences prior to actual execution on a superscalar microarchitecture; this opened up for dynamic scheduling of buffered partial instructions and enabled more parallelism to be extracted compared to the more rigid methods used in the simpler P5 Pentium; it also simplified speculative execution and allowed higher clock frequencies compared to designs such as the advanced Cyrix 6x86.
The simplest processors are scalar processors. Each instruction executed by a scalar processor typically manipulates one or two data items at a time. By contrast, each instruction executed by a vector processor operates simultaneously on many data items. An analogy is the difference between scalar and vector arithmetic. A superscalar processor is a mixture of the two. Each instruction processes one data item, but there are multiple execution units within each CPU thus multiple instructions can be processing separate data items concurrently.
Superscalar CPU design emphasizes improving the instruction dispatcher accuracy and allowing it to keep the multiple execution units in use at all times. This has become increasingly important as the number of units has increased. While early superscalar CPUs would have two ALUs and a single FPU, a later design such as the PowerPC 970 includes four ALUs, two FPUs, and two SIMD units. If the dispatcher is ineffective at keeping all of these units fed with instructions, the performance of the system will be no better than that of a simpler, cheaper design.
A superscalar processor usually sustains an execution rate in excess of one instruction per machine cycle. But merely processing multiple instructions concurrently does not make an architecture superscalar, since pipelined, multiprocessor or multi-core architectures also achieve that, but with different methods.
In a superscalar CPU the dispatcher reads instructions from memory and decides which ones can be run in parallel, dispatching each to one of the several execution units contained inside a single CPU. Therefore, a superscalar processor can be envisioned as having multiple parallel pipelines, each of which is processing instructions simultaneously from a single instruction thread.
Most modern superscalar CPUs also have logic to reorder the instructions to try to avoid pipeline stalls and increase parallel execution.
Available performance improvement from superscalar techniques is limited by three key areas:
Existing binary executable programs have varying degrees of intrinsic parallelism. In some cases instructions are not dependent on each other and can be executed simultaneously. In other cases they are inter-dependent: one instruction impacts either resources or results of the other. The instructions a = b + c; d = e + f
can be run in parallel because none of the results depend on other calculations. However, the instructions a = b + c; b = e + f
might not be runnable in parallel, depending on the order in which the instructions complete while they move through the units.
Although the instruction stream may contain no inter-instruction dependencies, a superscalar CPU must nonetheless check for that possibility, since there is no assurance otherwise and failure to detect a dependency would produce incorrect results.
No matter how advanced the semiconductor process or how fast the switching speed, this places a practical limit on how many instructions can be simultaneously dispatched. While process advances will allow ever greater numbers of execution units (e.g. ALUs), the burden of checking instruction dependencies grows rapidly, as does the complexity of register renaming circuitry to mitigate some dependencies. Collectively the power consumption, complexity and gate delay costs limit the achievable superscalar speedup.
However even given infinitely fast dependency checking logic on an otherwise conventional superscalar CPU, if the instruction stream itself has many dependencies, this would also limit the possible speedup. Thus the degree of intrinsic parallelism in the code stream forms a second limitation.
Collectively, these limits drive investigation into alternative architectural changes such as very long instruction word (VLIW), explicitly parallel instruction computing (EPIC), simultaneous multithreading (SMT), and multi-core computing.
With VLIW, the burdensome task of dependency checking by hardware logic at run time is removed and delegated to the compiler. Explicitly parallel instruction computing (EPIC) is like VLIW with extra cache prefetching instructions.
Simultaneous multithreading (SMT) is a technique for improving the overall efficiency of superscalar processors. SMT permits multiple independent threads of execution to better utilize the resources provided by modern processor architectures. The fact that they are independent means that we know that the instruction of one thread can be executed out of order and/or in parallel with the instruction of a different one. Also, one independent thread will not produce a pipeline bubble in the code stream of a different one, for example, due to a branch.
Superscalar processors differ from multi-core processors in that the several execution units are not entire processors. A single processor is composed of finer-grained execution units such as the ALU, integer multiplier, integer shifter, FPU, etc. There may be multiple versions of each execution unit to enable the execution of many instructions in parallel. This differs from a multi-core processor that concurrently processes instructions from multiple threads, one thread per processing unit (called "core"). It also differs from a pipelined processor, where the multiple instructions can concurrently be in various stages of execution, assembly-line fashion.
The various alternative techniques are not mutually exclusive—they can be (and frequently are) combined in a single processor. Thus a multicore CPU is possible where each core is an independent processor containing multiple parallel pipelines, each pipeline being superscalar. Some processors also include vector capability.
A central processing unit (CPU), also called a central processor, main processor, or just processor, is the most important processor in a given computer. Its electronic circuitry executes instructions of a computer program, such as arithmetic, logic, controlling, and input/output (I/O) operations. This role contrasts with that of external components, such as main memory and I/O circuitry, and specialized coprocessors such as graphics processing units (GPUs).
Very long instruction word (VLIW) refers to instruction set architectures that are designed to exploit instruction-level parallelism (ILP). A VLIW processor allows programs to explicitly specify instructions to execute in parallel, whereas conventional central processing units (CPUs) mostly allow programs to specify instructions to execute in sequence only. VLIW is intended to allow higher performance without the complexity inherent in some other designs.
IA-64 is the instruction set architecture (ISA) of the discontinued Itanium family of 64-bit Intel microprocessors. The basic ISA specification originated at Hewlett-Packard (HP), and was subsequently implemented by Intel in collaboration with HP. The first Itanium processor, codenamed Merced, was released in 2001.
Parallel computing is a type of computation in which many calculations or 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 has gained 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.
Flynn's taxonomy is a classification of computer architectures, proposed by Michael J. Flynn in 1966 and extended in 1972. The classification system has stuck, and it has been used as a tool in the design of modern processors and their functionalities. Since the rise of multiprocessing central processing units (CPUs), a multiprogramming context has evolved as an extension of the classification system. Vector processing, covered by Duncan's taxonomy, is missing from Flynn's work because the Cray-1 was released in 1977: Flynn's second paper was published in 1972.
Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically, ILP refers to the average number of instructions run per step of this parallel execution.
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 use the resources provided by modern processor architectures.
In the domain of central processing unit (CPU) design, hazards are problems with the instruction pipeline in CPU microarchitectures when the next instruction cannot execute in the following clock cycle, and can potentially lead to incorrect computation results. Three common types of hazards are data hazards, structural hazards, and control hazards.
In the history of computer hardware, some early reduced instruction set computer central processing units used a very similar architectural solution, now called a classic RISC pipeline. Those CPUs were: MIPS, SPARC, Motorola 88000, and later the notional CPU DLX invented for education.
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.
In computer engineering, out-of-order execution is a paradigm used in high-performance central processing units to make use of instruction cycles that would otherwise be wasted. In this paradigm, a processor executes instructions in an order governed by the availability of input data and execution units, rather than by their original order in a program. In doing so, the processor can avoid being idle while waiting for the preceding instruction to complete and can, in the meantime, process the next instructions that are able to run immediately and independently.
In computing, a pipeline, also known as a data pipeline, is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements.
In electronics, computer science and 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.
The Fujitsu FR-V is one of the very few processors ever able to process both a very long instruction word (VLIW) and vector processor instructions at the same time, increasing throughput with high parallel computing while increasing performance per watt and hardware efficiency. The family was presented in 1999. Its design was influenced by the VPP500/5000 models of the Fujitsu VP/2000 vector processor supercomputer line.
Scalar processors are a class of computer processors that process only one data item at a time. Typical data items include integers and floating point numbers.
A shelving buffer is a technique used in computer processors to increase the efficiency of superscalar processors. It allows for multiple instructions to be dispatched at once regardless of the data dependencies between those instructions. This allows for out-of-order execution to occur which increases the throughput of the microprocessor.
The history of general-purpose CPUs is a continuation of the earlier history of computing hardware.
In computer architecture, multithreading is the ability of a central processing unit (CPU) to provide multiple threads of execution.
Explicit data graph execution, or EDGE, is a type of instruction set architecture (ISA) which intends to improve computing performance compared to common processors like the Intel x86 line. EDGE combines many individual instructions into a larger group known as a "hyperblock". Hyperblocks are designed to be able to easily run in parallel.
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.
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