Single Instruction, Multiple Threads
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Single Instruction, Multiple Threads
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step. The SIMT execution model has been implemented on several GPUs and is relevant for general-purpose computing on graphics processing units (GPGPU), e.g. some supercomputers combine CPUs with GPUs. The processors, say a number of them, seem to execute many more than tasks. This is achieved by each processor having multiple "threads" (or "work-items" or "Sequence of SIMD Lane operations"), which execute in lock-step, and are analogous to SIMD lanes. The simplest way to understand SIMT is to imagine a multi-core system, where each core has its own register file, its own ALUs (both SIMD and Scalar) and its own data cache, but that unlike a standard multi-core system which has multiple independent instruction caches and d ...
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Parallel Computing
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.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather than m ...
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GDDR SDRAM
Graphics DDR SDRAM (GDDR SDRAM) is a type of synchronous dynamic random-access memory (SDRAM) specifically designed for applications requiring high bandwidth, e.g. graphics processing units (GPUs). GDDR SDRAM is distinct from the more widely known types of DDR SDRAM, such as DDR4 SDRAM, DDR4, although they share some of the same features—including double data rate data transfers. , GDDR SDRAM has been succeeded by GDDR2, GDDR3, GDDR4, GDDR5, GDDR5X, GDDR6, and GDDR6X. Generations File:ATI Radeon X1300 256MB - Hynix HY5DU561622CTP-5-5390.jpg, SK Hynix, Hynix GDDR SDRAM File:SAMSUNG@QDDR3-SDRAM@256MBit@K5J55323QF-GC16 Stack-DSC01234-DSC01284 - ZS-retouched.jpg, A Samsung GDDR3 256MBit package File:Sapphire Ultimate HD 4670 512MB - Qimonda HYB18H512321BF-10-93577.jpg, A 512 MBit Qimonda GDDR3 SDRAM package File:SAMSUNG@QDDR3-SDRAM@256MBit@K5J55323QF-GC16 Stack-DSC01340-DSC01367 - ZS-retouched.jpg, Inside a Samsung GDDR3 256MBit package DDR SGRAM GDDR was initially known as ...
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Parallel Computing
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.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather than m ...
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GPGPU
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing. Essentially, a GPGPU pipeline is a kind of parallel processing between one or more GPUs and CPUs that analyzes data as if it were in image or other graphic form. While GPUs operate at lower frequencies, they typically have many times the number of cores. Thus, GPUs can process far more pictures and graphical data per second than a traditional CPU. Migrating data into graphical form and then using the GPU to scan and analyze it can create a large speedup. GPGPU pipelines were developed at the beginning of the 21st century for graphic ...
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Computer Architecture
In computer engineering, computer architecture is a description of the structure of a computer system made from component parts. It can sometimes be a high-level description that ignores details of the implementation. At a more detailed level, the description may include the instruction set architecture design, microarchitecture design, logic design, and implementation. History The first documented computer architecture was in the correspondence between Charles Babbage and Ada Lovelace, describing the analytical engine. When building the computer Z1 in 1936, Konrad Zuse described in two patent applications for his future projects that machine instructions could be stored in the same storage used for data, i.e., the stored-program concept. Two other early and important examples are: * John von Neumann's 1945 paper, First Draft of a Report on the EDVAC, which described an organization of logical elements; and *Alan Turing's more detailed ''Proposed Electronic Calculator'' ...
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Classes Of Computers
Computers can be classified, or typed, in many ways. Some common classifications of computers are given below. Classes by purpose , - , style="text-align: left;", Notes: Microcomputers (personal computers) Microcomputers became the most common type of computer in the late 20th century. The term “microcomputer” was introduced with the advent of systems based on single-chip microprocessors. The best-known early system was the Altair 8800, introduced in 1975. The term "microcomputer" has practically become an anachronism as it has fallen into disuse. These computers include: * Desktop computers – A case put under or on a desk. The display may be optional, depending on use. The case size may vary, depending on the required expansion slots. Very small computers of this kind may be integrated into the monitor. * Rackmount computers – The cases of these computers fit into 19-inch racks, and maybe space-optimized and very flat. A dedicated display, keyboar ...
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General-purpose Computing On Graphics Processing Units
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing. Essentially, a GPGPU pipeline is a kind of parallel processing between one or more GPUs and CPUs that analyzes data as if it were in image or other graphic form. While GPUs operate at lower frequencies, they typically have many times the number of cores. Thus, GPUs can process far more pictures and graphical data per second than a traditional CPU. Migrating data into graphical form and then using the GPU to scan and analyze it can create a large speedup. GPGPU pipelines were developed at the beginning of the 21st century for graphi ...
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Graphics Core Next
Graphics Core Next (GCN) is the codename for a series of microarchitectures and an instruction set architecture that were developed by AMD for its GPUs as the successor to its TeraScale microarchitecture. The first product featuring GCN was launched on January 9, 2012. GCN is a reduced instruction set SIMD microarchitecture contrasting the very long instruction word SIMD architecture of TeraScale. GCN requires considerably more transistors than TeraScale, but offers advantages for general-purpose GPU (GPGPU) computation due to a simpler compiler. GCN graphics chips were fabricated with CMOS at 28 nm, and with FinFET at 14 nm (by Samsung Electronics and GlobalFoundries) and 7 nm (by TSMC), available on selected models in AMD's Radeon HD 7000, HD 8000, 200, 300, 400, 500 and Vega series of graphics cards, including the separately released Radeon VII. GCN was also used in the graphics portion of Accelerated Processing Units (APUs), such as those in the PlayStation 4 and Xb ...
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OpenCL
OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. OpenCL specifies programming languages (based on C99, C++14 and C++17) for programming these devices and application programming interfaces (APIs) to control the platform and execute programs on the compute devices. OpenCL provides a standard interface for parallel computing using task- and data-based parallelism. OpenCL is an open standard maintained by the non-profit technology consortium Khronos Group. Conformant implementations are available from Altera, AMD, ARM, Creative, IBM, Imagination, Intel, Nvidia, Qualcomm, Samsung, Vivante, Xilinx, and ZiiLABS. Overview OpenCL views a computing system as consisting of a number of ''compute devices'', which migh ...
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CUDA
CUDA (or Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for general purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements, for the execution of compute kernels. CUDA is designed to work with programming languages such as C, C++, and Fortran. This accessibility makes it easier for specialists in parallel programming to use GPU resources, in contrast to prior APIs like Direct3D and OpenGL, which required advanced skills in graphics programming. CUDA-powered GPUs also support programming frameworks such as OpenMP, OpenACC and OpenCL; and HIP by compiling such code to CUDA. CUDA was created by Nvidia. When it was first introduced, the name was an acronym for Compute Unified Device Architectur ...
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Multi-core Processor
A multi-core processor is a microprocessor on a single integrated circuit with two or more separate processing units, called cores, each of which reads and executes program instructions. The instructions are ordinary CPU instructions (such as add, move data, and branch) but the single processor can run instructions on separate cores at the same time, increasing overall speed for programs that support multithreading or other parallel computing techniques. Manufacturers typically integrate the cores onto a single integrated circuit die (known as a chip multiprocessor or CMP) or onto multiple dies in a single chip package. The microprocessors currently used in almost all personal computers are multi-core. A multi-core processor implements multiprocessing in a single physical package. Designers may couple cores in a multi-core device tightly or loosely. For example, cores may or may not share caches, and they may implement message passing or shared-memory inter-core communica ...
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Multithreading (computer Architecture)
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). 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 combined in nearly all modern systems architectures with multiple multithreading CPUs and with CPUs with multiple multithreading cores. Overview The multithreading paradigm has become more popular as efforts to further exploit instruction-level p ...
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