Superscalar processor

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Simple superscalar pipeline. By fetching and dispatching two instructions at a time, a maximum of two instructions per cycle can be completed. (IF = Instruction Fetch, ID = Instruction Decode, EX = Execute, MEM = Memory access, WB = Register write back, i = Instruction number, t = Clock cycle [i.e., time]) Superscalarpipeline.svg
Simple superscalar pipeline. By fetching and dispatching two instructions at a time, a maximum of two instructions per cycle can be completed. (IF = Instruction Fetch, ID = Instruction Decode, EX = Execute, MEM = Memory access, WB = Register write back, i = Instruction number, t = Clock cycle [i.e., time])
Processor board of a CRAY T3e supercomputer with four superscalar Alpha 21164 processors Processor board cray-2 hg.jpg
Processor board of a CRAY T3e supercomputer with four superscalar Alpha 21164 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 (the number of instructions that can be executed in a unit of time) than would otherwise be not 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.

Central processing unit electronic circuitry within a computer that carries out the instructions of a computer program by performing the basic arithmetic, logical, control and input/output (I/O) operations specified by the instructions

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.

Instruction-level parallelism ability of computer instructions to be executed simultaneously with correct results

Instruction-level parallelism (ILP) is a measure of how many of the instructions in a computer program can be executed simultaneously.

Scalar processors represent a class of computer processors. A scalar processor processes only one data item at a time, with typical data items being integers or floating point numbers. A scalar processor is classified as a SISD processor in Flynn's taxonomy.

Contents

In Flynn's taxonomy, a single-core superscalar processor is classified as an SISD processor (Single Instruction stream, Single Data stream), though a single-core superscalar processor that supports short vector operations could be classified as SIMD (Single Instruction stream, Multiple Data streams). A multi-core superscalar processor is classified as an MIMD processor (Multiple Instruction streams, Multiple Data streams).

Flynn's taxonomy is a classification of computer architectures, proposed by Michael J. Flynn in 1966. The classification system has stuck, and has been used as a tool in 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.

SISD class of computer architecture in Flynns taxonomy

In computing, SISD is a computer architecture in which a single uni-core processor, executes a single instruction stream, to operate on data stored in a single memory. This corresponds to the von Neumann architecture.

SIMD class of parallel computers in Flynns taxonomy, with multiple processing elements that perform the same operation on multiple data points simultaneously

Single instruction, multiple data (SIMD) is a class of parallel computers in Flynn's taxonomy. It describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. Such machines exploit data level parallelism, but not concurrency: there are simultaneous (parallel) computations, but only a single process (instruction) at a given moment. SIMD is particularly applicable to common tasks such as adjusting the contrast in a digital image or adjusting the volume of digital audio. Most modern CPU designs include SIMD instructions to improve the performance of multimedia use. SIMD is not to be confused with SIMT, which utilizes threads.

While a superscalar CPU is typically also pipelined, superscalar and pipelining execution are considered different performance enhancement techniques. The former executes multiple instructions in parallel by using multiple execution units, whereas the latter executes multiple instructions in the same execution unit in parallel by dividing the execution unit into different phases.

The superscalar technique is traditionally associated with several identifying characteristics (within a given CPU):

In computer science, compile time refers to either the operations performed by a compiler, programming language requirements that must be met by source code for it to be successfully compiled, or properties of the program that can be reasoned about during compilation. Compile time refers to the time duration during which the statements written in any programming language are checked for errors.

History

Seymour Cray's CDC 6600 from 1966 is often mentioned as the first superscalar design. The 1967 IBM System/360 Model 91 was another superscalar mainframe. The Motorola MC88100 (1988), the Intel i960CA (1989) and the AMD 29000-series 29050 (1990) 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 (this was why RISC designs were faster than CISC designs through the 1980s and into the 1990s).

Seymour Cray Applied mathematician, computer scientist, and electrical engineer

Seymour Roger Cray was an American electrical engineer and supercomputer architect who designed a series of computers that were the fastest in the world for decades, and founded Cray Research which built many of these machines. Called "the father of supercomputing", Cray has been credited with creating the supercomputer industry. Joel S. Birnbaum, then chief technology officer of Hewlett-Packard, said of him: "It seems impossible to exaggerate the effect he had on the industry; many of the things that high performance computers now do routinely were at the farthest edge of credibility when Seymour envisioned them." Larry Smarr, then director of the National Center for Supercomputing Applications at the University of Illinois and a physicist, linking him: "He [Seymour Cray] is the Thomas Edison of the supercomputing industry."

CDC 6600 computer

The CDC 6600 was the flagship of the 6000 series of mainframe computer systems manufactured by Control Data Corporation. Generally considered to be the first successful supercomputer, it outperformed the industry's prior recordholder, the IBM 7030 Stretch, by a factor of three. With performance of up to three megaFLOPS, the CDC 6600 was the world's fastest computer from 1964 to 1969, when it relinquished that status to its successor, the CDC 7600.

IBM System/360 Model 91 model of computer

The IBM System/360 Model 91 was announced in 1964 as a competitor to the CDC 6600. Functionally, the Model 91 ran like any other large-scale System/360, but the internal organization was the most advanced of the System/360 line, and it was the first IBM computer to support out-of-order instruction execution. It ran OS/360 as its operating system. It was designed to handle high-speed data processing for scientific applications. This included space exploration, theoretical astronomy, sub-atomic physics and global weather forecasting.

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.

Low-power electronics are electronics, such as notebook processors, that have been designed to use less electric power.

Embedded system computer system with a dedicated function within a larger mechanical or electrical system

An embedded system is a controller programmed and controlled by a real-time operating system (RTOS) with a dedicated function within a larger mechanical or electrical system, often with real-time computing constraints. It is embedded as part of a complete device often including hardware and mechanical parts. Embedded systems control many devices in common use today. Ninety-eight percent of all microprocessors manufactured are used in embedded systems.

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.

Scalar to superscalar

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 having multiple parallel pipelines, each of which is processing instructions simultaneously from a single instruction thread.

Limitations

Available performance improvement from superscalar techniques is limited by three key areas:

  1. The degree of intrinsic parallelism in the instruction stream (instructions requiring the same computational resources from the CPU).
  2. The complexity and time cost of dependency checking logic and register renaming circuitry
  3. The branch instruction processing.

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.

When the number of simultaneously issued instructions increases, the cost of dependency checking increases extremely rapidly. This is exacerbated by the need to check dependencies at run time and at the CPU's clock rate. This cost includes additional logic gates required to implement the checks, and time delays through those gates. Research[ citation needed ] shows the gate cost in some cases may be gates, and the delay cost , where is the number of instructions in the processor's instruction set, and is the number of simultaneously dispatched instructions.

Even though 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 to roughly eight simultaneously dispatched instructions.

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.

Alternatives

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.

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 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.

See also

Related Research Articles

Very long instruction word (VLIW) refers to instruction set architectures designed to exploit instruction level parallelism (ILP). Whereas conventional central processing units mostly allow programs to specify instructions to execute in sequence only, a VLIW processor allows programs to explicitly specify instructions to execute in parallel. This design is intended to allow higher performance without the complexity inherent in some other designs.

In computing, a vector processor or array processor is a central processing unit (CPU) that implements an instruction set containing instructions that operate on one-dimensional arrays of data called vectors, compared to the scalar processors, whose instructions operate on single data items. Vector processors can greatly improve performance on certain workloads, notably numerical simulation and similar tasks. Vector machines appeared in the early 1970s and dominated supercomputer design through the 1970s into the 1990s, notably the various Cray platforms. The rapid fall in the price-to-performance ratio of conventional microprocessor designs led to the vector supercomputer's demise in the later 1990s.

Parallel computing programming paradigm in which many calculations or the execution of processes are carried out simultaneously

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.

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.

In computing, SPMD is a technique employed to achieve parallelism; it is a subcategory of MIMD. Tasks are split up and run simultaneously on multiple processors with different input in order to obtain results faster. SPMD is the most common style of parallel programming. It is also a prerequisite for research concepts such as active messages and distributed shared memory.

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.

Microarchitecture the way a given instruction set architecture (ISA) is implemented on a processor

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.

In computer architecture, a transport triggered architecture (TTA) is a kind of processor design in which programs directly control the internal transport buses of a processor. Computation happens as a side effect of data transports: writing data into a triggering port of a functional unit triggers the functional unit to start a computation. This is similar to what happens in a systolic array. Due to its modular structure, TTA is an ideal processor template for application-specific instruction-set processors (ASIP) with customized datapath but without the inflexibility and design cost of fixed function hardware accelerators.

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.

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.

Task parallelism is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism which involves running the same task on different components of data, task parallelism is distinguished by running many different tasks at the same time on the same data. A common type of task parallelism is pipelining which consists of moving a single set of data through a series of separate tasks where each task can execute independently of the others.

The history of general-purpose CPUs is a continuation of the earlier history of computing hardware.

Multithreading (computer architecture) ability of a central processing unit (CPU) or a single core in a multi-core processor to execute multiple processes or threads concurrently

In computer architecture, multithreading is the ability of a central processing unit (CPU) 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).

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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