Warp (CUDA)
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Warp (CUDA)
A thread block is a programming abstraction that represents a group of threads that can be executed serially or in parallel. For better process and data mapping, threads are grouped into thread blocks. The number of threads in a thread block was formerly limited by the architecture to a total of 512 threads per block, but as of March 2010, with compute capability 2.x and higher, blocks may contain up to 1024 threads. The threads in the same thread block run on the same stream processor. Threads in the same block can communicate with each other via shared memory, barrier synchronization or other synchronization primitives such as atomic operations. Multiple blocks are combined to form a grid. All the blocks in the same grid contain the same number of threads. The number of threads in a block is limited, but grids can be used for computations that require a large number of thread blocks to operate in parallel and to use all available multiprocessors. CUDA is a parallel computing ...
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Thread (computing)
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. In Modern Operating Systems, Tanenbaum shows that many distinct models of process organization are possible.TANENBAUM, Andrew S. Modern Operating Systems. 1992. Prentice-Hall International Editions, ISBN 0-13-595752-4. In many cases, a thread is a component of a process. The multiple threads of a given process may be executed concurrently (via multithreading capabilities), 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. History Threads made an early appearance under the name of "tasks ...
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Instruction-level Parallelism
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. Discussion ILP must not be confused with concurrency. In ILP there is a single specific thread of execution of a process. On the other hand, concurrency involves the assignment of multiple threads to a CPU's core in a strict alternation, or in true parallelism if there are enough CPU cores, ideally one core for each runnable thread. There are two approaches to instruction-level parallelism: hardware and software. Hardware level works upon dynamic parallelism, whereas the software level works on static parallelism. Dynamic parallelism means the processor decides at run time which instructions to execute in parallel, whereas static parallelism means the compiler decides which instructions to execute in parallel. The Pentium processor wor ...
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Least Recently Used
In computing, cache algorithms (also frequently called cache replacement algorithms or cache replacement policies) are optimizing instructions, or algorithms, that a computer program or a hardware-maintained structure can utilize in order to manage a cache of information stored on the computer. Caching improves performance by keeping recent or often-used data items in memory locations that are faster or computationally cheaper to access than normal memory stores. When the cache is full, the algorithm must choose which items to discard to make room for the new ones. Overview The average memory reference time is : T = m \times T_m + T_h + E where : m = miss ratio = 1 - (hit ratio) : T_m = time to make a main memory access when there is a miss (or, with multi-level cache, average memory reference time for the next-lower cache) : T_h= the latency: the time to reference the cache (should be the same for hits and misses) : E = various secondary effects, such as queuing effects in mult ...
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Round-robin Scheduling
Round-robin (RR) is one of the algorithms employed by process and network schedulers in computing.Guowang Miao, Jens Zander, Ki Won Sung, and Ben Slimane, Fundamentals of Mobile Data Networks, Cambridge University Press, , 2016. As the term is generally used, time slices (also known as time quanta) are assigned to each process in equal portions and in circular order, handling all processes without priority (also known as cyclic executive). Round-robin scheduling is simple, easy to implement, and starvation-free. Round-robin scheduling can be applied to other scheduling problems, such as data packet scheduling in computer networks. It is an operating system concept. The name of the algorithm comes from the round-robin principle known from other fields, where each person takes an equal share of something in turn. Process scheduling To schedule processes fairly, a round-robin scheduler generally employs time-sharing, giving each job a time slot or ''quantum'' (its allowance ...
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Scheduling Policy
In computing, scheduling is the action of assigning ''resources'' to perform ''tasks''. The ''resources'' may be processors, network links or expansion cards. The ''tasks'' may be threads, processes or data flows. The scheduling activity is carried out by a process called scheduler. Schedulers are often designed so as to keep all computer resources busy (as in load balancing), allow multiple users to share system resources effectively, or to achieve a target quality-of-service. Scheduling is fundamental to computation itself, and an intrinsic part of the execution model of a computer system; the concept of scheduling makes it possible to have computer multitasking with a single central processing unit (CPU). Goals A scheduler may aim at one or more goals, for example: * maximizing ''throughput'' (the total amount of work completed per time unit); * minimizing '' wait time'' (time from work becoming ready until the first point it begins execution); * minimizing '' latency ...
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Context Switching
In computing, a context switch is the process of storing the state of a process or thread, so that it can be restored and resume execution at a later point, and then restoring a different, previously saved, state. This allows multiple processes to share a single central processing unit (CPU), and is an essential feature of a multitasking operating system. The precise meaning of the phrase "context switch" varies. In a multitasking context, it refers to the process of storing the system state for one task, so that task can be paused and another task resumed. A context switch can also occur as the result of an interrupt, such as when a task needs to access disk storage, freeing up CPU time for other tasks. Some operating systems also require a context switch to move between user mode and kernel mode tasks. The process of context switching can have a negative impact on system performance. Cost Context switches are usually computationally intensive, and much of the design of o ...
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Process (computing)
In computing, a process is the instance of a computer program that is being executed by one or many threads. There are many different process models, some of which are light weight, but almost all processes (even entire virtual machines) are rooted in an operating system (OS) process which comprises the program code, assigned system resources, physical and logical access permissions, and data structures to initiate, control and coordinate execution activity. Depending on the OS, a process may be made up of multiple threads of execution that execute instructions concurrently. While a computer program is a passive collection of instructions typically stored in a file on disk, a process is the execution of those instructions after being loaded from the disk into memory. Several processes may be associated with the same program; for example, opening up several instances of the same program often results in more than one process being executed. Multitasking is a method to allow ...
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Nvidia
Nvidia CorporationOfficially written as NVIDIA and stylized in its logo as VIDIA with the lowercase "n" the same height as the uppercase "VIDIA"; formerly stylized as VIDIA with a large italicized lowercase "n" on products from the mid 1990s to early-mid 2000s. Though unofficial, second letter capitalization of NVIDIA, i.e. nVidia, may be found within enthusiast communities and publications. ( ) is an American multinational technology company incorporated in Delaware and based in Santa Clara, California. It is a software and fabless company which designs graphics processing units (GPUs), application programming interface (APIs) for data science and high-performance computing as well as system on a chip units (SoCs) for the mobile computing and automotive market. Nvidia is a global leader in artificial intelligence hardware and software. Its professional line of GPUs are used in workstations for applications in such fields as architecture, engineering and construction, media ...
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Texture Cache
This is a glossary of terms relating to computer graphics. For more general computer hardware terms, see glossary of computer hardware terms. 0–9 A B C D E F G H I K L M N O P Q R S T ...
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Shared Memory
In computer science, shared memory is memory that may be simultaneously accessed by multiple programs with an intent to provide communication among them or avoid redundant copies. Shared memory is an efficient means of passing data between programs. Depending on context, programs may run on a single processor or on multiple separate processors. Using memory for communication inside a single program, e.g. among its multiple threads, is also referred to as shared memory. In hardware In computer hardware, ''shared memory'' refers to a (typically large) block of random access memory (RAM) that can be accessed by several different central processing units (CPUs) in a multiprocessor computer system. Shared memory systems may use: * uniform memory access (UMA): all the processors share the physical memory uniformly; * non-uniform memory access (NUMA): memory access time depends on the memory location relative to a processor; * cache-only memory architecture (COMA): the local memo ...
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Cache (computing)
In computing, a cache ( ) is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A ''cache hit'' occurs when the requested data can be found in a cache, while a ''cache miss'' occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs. To be cost-effective and to enable efficient use of data, caches must be relatively small. Nevertheless, caches have proven themselves in many areas of computing, because typical computer applications access data with a high degree of locality of reference. Such access patterns exhibit temporal locality, where data is requested that has been recently requested already, and spatial locality, where d ...
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