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Parallelization across multiple processors in parallel computing environments
Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different
Data_parallelism
Abstraction of parallel computer architecture
Flynn's taxonomy, data parallelism is usually classified as MIMD/SPMD or SIMD. Stream parallelism, also known as pipeline parallelism, focuses on dividing
Parallel_programming_model
Object-oriented programming language extension for Java
Data parallelism features can also be implemented by libraries using dedicated data structures, such as parallel arrays. The term task parallelism is
Ateji_PX
Programming paradigm in which many processes are executed simultaneously
forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but
Parallel_computing
Form of parallelization of computer code
parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism
Task_parallelism
Central computer component that executes instructions
CPUs devote a lot of semiconductor area to caches and instruction-level parallelism to increase performance and to CPU modes to support operating systems
Central_processing_unit
important new ideas behind NESL are Nested data parallelism: this feature offers the benefits of data parallelism, concise code that is easy to understand
NESL
Class of parallel computing applications
computing. Data-parallelism applied computation independently to each data item of a set of data, which allows the degree of parallelism to be scaled with
Data-intensive_computing
Compiler transformation of sequential programs for parallel execution
analysis, alias analysis and data-flow analysis, together with program transformations that expose or increase usable parallelism. Loops have historically
Automatic_parallelization
Stylistic device characteristic of LLMs
use negative parallelism to the extent that they do, a few explanations have been suggested: Such constructions are frequent in training data. During reinforcement
Negative_parallelism
Data processing chain
fashion can handle the building and running of big data pipelines. Dataflow Throughput Parallelism Instruction pipeline Classic RISC pipeline Graphics
Pipeline_(computing)
Type of data structure
with statically predictable access patterns are a major source of data parallelism. Dynamic arrays or growable arrays are similar to arrays but add the
Array_(data_structure)
transformation is an algorithm that transforms nested data parallelism into flat data parallelism. It was pioneered by Guy Blelloch as part of the NESL
Flattening_transformation
Chinese artificial intelligence company
Distributed Data Parallel (DDP): Parallel training library that implements various forms of parallelism such as data parallelism (DP), pipeline parallelism (PP)
DeepSeek
Measure of the amount of work needed to perform a computing task
process the bulk of the data while others might be idle. Further, coarse-grained parallelism fails to exploit the parallelism in the program as most of
Granularity (parallel computing)
Granularity_(parallel_computing)
Programming language
on how parallelism can be expressed in order to enable more aggressive compiler optimisations. In particular, irregular nested data parallelism is not
Futhark (programming language)
Futhark_(programming_language)
Physical components of a computer
able to implement data parallelism, thread-level parallelism and request-level parallelism (both implementing task-level parallelism). Microarchitecture
Computer_hardware
Open-source data analytics cluster computing framework
analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally
Apache_Spark
The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures. Where a sequential
Loop-level_parallelism
DirectX 11 and an open specification from Microsoft for implementing data parallelism directly in C++. It is intended to make programming GPUs easy for the
C++_AMP
Dataflow-based graph execution model.
"hyperblock". Hyperblocks are designed to be able to easily run in parallel. Parallelism of modern CPU designs generally starts to plateau at about eight internal
Explicit_data_graph_execution
Machine learning model for speech
SpecAugment, Stochastic Depth, and BPE Dropout. The training used data parallelism with float16, dynamic loss scaling, and activation checkpointing. After
Whisper (speech recognition system)
Whisper_(speech_recognition_system)
Family of microprocessors
(ADI). It is superscalar and features data-parallelism in the form of short-vector SIMD and subword (16-bit) parallelism (SWAR). It consists of: Two separate
TigerSHARC
Facilities containing Google servers
Maximize parallelism, such as by splitting a single document match lookup in a large index into a MapReduce over many small indices. Partition index data and
Google_data_centers
American semiconductor company
system with 13.6 million cores for natural-language processing. It uses data parallelism to train. In October 2022, Sandia National Laboratories of the National
Cerebras_Systems
American technology company
designed off on two key observations: AI workloads exhibit substantial data parallelism, which can be mapped onto purpose-built hardware, leading to performance
Groq
Ability of computer instructions to be executed simultaneously with correct results
Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically,
Instruction-level_parallelism
Type of parallel processing
but it should not be confused with an ISA. Such machines exploit data level parallelism, but not concurrency: there are simultaneous (parallel) computations
Single instruction, multiple data
Single_instruction,_multiple_data
technique is used when a loop cannot be fully parallelized by DOALL parallelism due to data dependencies between loop iterations, typically loop-carried dependencies
DOACROSS_parallelism
size N. As in this example, scalable parallelism is typically a form of data parallelism. This form of parallelism is often the target of automatic parallelization
Scalable_parallelism
Procedure in computing
volumes of data. ETL applications implement three main types of parallelism: Data: By splitting a single sequential file into smaller data files to provide
Extract,_transform,_load
Algorithm for modelling sequential data
because their parameters, activations, and training data may not fit on a single device. Data parallelism copies the model across devices and splits different
Transformer_(deep_learning)
Computer hardware technology that uses quantum mechanics
with a quantum state in superposition, sometimes referred to as quantum parallelism. Peter Shor built on these results in 1994 with polynomial-time quantum
Quantum_computing
Array of processing elements specialized for parallelizable workloads
running very large kernels through the exploitation of scalable parallelism and data reuse. Consider a kernel, i.e. a function to be applied to several
Spatial_architecture
Computer scientist
Keller is a computer scientist whose research concerns type systems and data parallelism in functional programming. Educated in Germany, she has worked in Australia
Gabriele_Keller
Scientific visualization software
Visualization Toolkit (VTK) libraries. ParaView is an application designed for data parallelism on shared-memory or distributed-memory multicomputers and clusters
ParaView
Open standard for parallelizing
thread executes its allocated part of the code. Both task parallelism and data parallelism can be achieved using OpenMP in this way. The runtime environment
OpenMP
Method of analyzing variables in software
S2CID 5955667. Knoop, Jens; Steffen, Bernhard; Vollmer, Jürgen (1996-05-01). "Parallelism for free: efficient and optimal bitvector analyses for parallel programs"
Data-flow_analysis
British semiconductor company
832 threads, respectively) "MIMD (Multiple Instruction, Multiple Data) parallelism and has distributed, local memory as its only form of memory on the
Graphcore
Topics referred to by the same term
Netherlands Data level parallelism, a form of data parallelism in computer science Data loss prevention, a field of computer security; See Data loss prevention
DLP
Series of convolutional neural networks for image classification
of C++ Caffe, modified for multi-GPU training and evaluation with data parallelism. On a system equipped with 4 NVIDIA Titan Black GPUs, training a single
VGGNet
Computing technique employed to achieve parallelism
In computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processor
Multiple instruction, multiple data
Multiple_instruction,_multiple_data
Use of a GPU for computations typically assigned to CPUs
games. C++ Accelerated Massive Parallelism (C++ AMP) is a library that accelerates execution of C++ code by exploiting the data-parallel hardware on GPUs.
General-purpose computing on graphics processing units
General-purpose_computing_on_graphics_processing_units
Set of computers configured in a distributed computing system
achieving task parallelism without multi-node cooperation, given that the main goal of the system is providing rapid user access to shared data. However, "computer
Computer_cluster
Component of computer engineering
EPIC types have been in fashion. Architectures that are dealing with data parallelism include SIMD and Vectors. Some labels used to denote classes of CPU
Microarchitecture
Free and open-source object relational database management system
NetBSD, and handles a range of workloads from single machines to data warehouses, data lakes, or web services with many concurrent users. The PostgreSQL
PostgreSQL
Sequence in computer science
parallel prefix operations form part of the formalization of the data parallelism model provided by machines such as the Connection Machine. The Connection
Prefix_sum
Class of artificial neural networks
standard data parallelism — where each GPU processes a separate sample — insufficient when individual graphs exceed single-device memory. Graph Parallelism addresses
Graph_neural_network
Rust software and development tools
high-performance web framework Diesel — ORM and query builder for Rust Rayon — data parallelism library for Rust Rocket — web framework focused on type safety Serde
List of Rust software and tools
List_of_Rust_software_and_tools
Parallel programming language
supporting abstractions for data parallelism, task parallelism, and nested parallelism. It enables optimizations for the locality of data and computation in the
Chapel_(programming_language)
Advanced interactive shell for Python
parallelism Multiple program, multiple data (MPMD) parallelism Message passing using MPI Task parallelism Data parallelism Combinations of these approaches
IPython
Data structure implementable in purely functional languages
unpredictability complicates the use of parallelism.[citation needed] In order to avoid those problems, some data structures allow for the inefficient operation
Purely functional data structure
Purely_functional_data_structure
2015 password-based key derivation function
multiple of 4*parallelism kibibytes blockCount ← Floor(memorySizeKB, 4*parallelism) Allocate two-dimensional array of 1 KiB blocks (parallelism rows x columnCount
Argon2
Topics referred to by the same term
predictive coding, a tool used in audio signal processing Warp (CUDA), data parallelism per instruction proposed by CUDA Warp (terminal), a command line terminal
Warp
Compiler for Haskell programming language
mutable arrays, unboxed data types, concurrent and parallel programming models (such as software transactional memory and data parallelism) and a profiler. Peyton
Glasgow_Haskell_Compiler
built on pbdMPI uses SPMD parallelism where every processor is considered as worker and owns parts of data. The SPMD parallelism introduced in mid 1980 is
Programming with Big Data in R
Programming_with_Big_Data_in_R
Large language model developed by Google
attached to 768 hosts, connected using a combination of model and data parallelism, which was the largest TPU configuration. This allowed for efficient
PaLM
Functional programming language for arrays
However, with arrays as its core data structure it provides opportunities for performance gains through parallelism, parallel computing, massively parallel
APL_(programming_language)
Type of parallel computing architecture of tightly coupled nodes
receives multiple data streams, and multiple data counters are needed to generate these data streams, it supports data parallelism. A major benefit of
Systolic_array
Computing technique used to achieve parallelism
single program, multiple data (SPMD) is a term that has been used to refer to computational models for exploiting parallelism whereby multiple processors
Single_program,_multiple_data
Computer programming paradigm
well over 50:1 and continues to increase with algorithmic complexity. Data parallelism, which exists in a kernel when the same function is applied to all
Stream_processing
Array data structure that compactly stores bits
set data structure. A bit array is effective at exploiting bit-level parallelism in hardware to perform operations quickly. A typical bit array stores
Bit_array
Programming situation where an instruction refers to a prior instruction's data
instruction 3 is also truly dependent on instruction 1. Instruction level parallelism is therefore not an option in this example. An anti-dependency occurs
Data_dependency
Low-power mobile multimedia processor
co-processors may be optimised for throughput over latency (more cores and data parallelism, but at a lower clock speed) and have instruction-sets and memory architectures
VideoCore
.NET managed concurrency library
queries on objects (LINQ to Objects) and XML data (LINQ to XML). PLINQ is intended for exposing data parallelism by use of queries. Any computation on objects
Parallel_Extensions
Interatomic potentials constructed by machine learning programs
multiple GPUs — a distinct strategy from data parallelism (which distributes training examples) or model parallelism (which distributes layers). This enabled
Machine-learned interatomic potential
Machine-learned_interatomic_potential
Computer software system
also suitable to being implemented in parallel processors by exploiting parallelism between different windows and/or within each window extent. Since there
Data_stream_management_system
Language) is a declarative, data-centric programming language designed in 2000 to allow a team of programmers to process big data across a high performance
ECL (data-centric programming language)
ECL_(data-centric_programming_language)
Software that provides access that hides details
(January 2011). "Using simple abstraction to reinvent computing for parallelism". Communications of the ACM. 54 (1): 75–85. doi:10.1145/1866739.1866757
Abstraction (computer science)
Abstraction_(computer_science)
General-purpose programming language
currentTimeMillis - t) + "ms") Besides futures and promises, actor support, and data parallelism, Scala also supports asynchronous programming with software transactional
Scala_(programming_language)
Parallel programming model
In computing, algorithmic skeletons, or parallelism patterns, are a high-level parallel programming model for parallel and distributed computing. Algorithmic
Algorithmic_skeleton
Design pattern in software development
operation for certain data types. This is known as multiple data parallelism. ‘Reduces’ or ‘scans’ are used to apply prefixes to a set of data, before then applying
Skeleton (computer programming)
Skeleton_(computer_programming)
Category of programming languages
programming Data-intensive computing Parallel computing Distributed computing Data parallelism Big Data (ECL, data-centric programming language for Big Data) Handbook
Data-centric programming language
Data-centric_programming_language
Message-passing system for parallel computers
and pbdMPI, where Rmpi focuses on manager-workers parallelism while pbdMPI focuses on SPMD parallelism. Both implementations fully support Open MPI or MPICH2
Message_Passing_Interface
AI that generates content
Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism". Findings of the Association for Computational Linguistics ACL 2024
Generative_AI
applications. Emphasis is laid on efficient support for array processing via data parallelism. Efficiency concerns are essentially twofold. First, efficiency in
SAC_programming_language
AMD computing architecture
accelerate signal processing and, more generally, applications where data parallelism could offer significant improvements. Initially, AI engines were released
AI_engine
CPU that implements instruction-level parallelism within a single processor
multiple-issue processor) is a CPU that implements a form of parallelism called instruction-level parallelism within a single processor. In contrast to a scalar
Superscalar_processor
data, and task parallelism. parameter In computer programming, a special kind of variable, used in a subroutine to refer to one of the pieces of data
Glossary_of_computer_science
Interface used for connecting storage devices
interface, has been designed to capitalize on the low latency and internal parallelism of solid-state storage devices. Architecturally, the logic for NVMe is
NVM_Express
Hardware cache of a central processing unit
cache (LLC). Additional techniques are used for increasing the level of parallelism when LLC is shared between multiple cores, including slicing it into
CPU_cache
Computer architecture to aid parallelism
of instruction set architecture designed to exploit instruction-level parallelism (ILP) by explicitly specifying, in advance, which instructions execute
Very_long_instruction_word
Computing concept
dataflow machines by Arvind. They use tags in memory to facilitate parallelism. Data flows around the computer through the components of the computer.
Dataflow
Open-source distributed stream processing
There are other comparable streaming data engines such as Spark Streaming and Flink. C++ AMP Data parallelism Lambda architecture Message passing OpenMP
Apache_Storm
Type of program in computer graphics
programmable operation which is applied to data as it moves through the rendering pipeline. Shaders act on data such as vertices and primitives, generate
Shader
Collusion between competitors
There are two types of tacit collusion: concerted action and conscious parallelism. In a concerted action, also known as concerted activity, competitors
Tacit_collusion
Theoretical speedup formula in computer architecture
where S {\displaystyle S} is the theoretical speedup of the program with parallelism (scaled speedup); N {\displaystyle N} is the number of processors; s
Gustafson's_law
Computer programming paradigm
read or debug. Explicit parallelism is one of the main reasons for the poor performance of Enterprise Java Beans when building data-intensive, non-OLTP applications
Dataflow_programming
Microprocessor architecture
parallelism by the capabilities of the compiler, not the on-chip systems. Whereas modern processors are reaching a plateau at four-wide parallelism,
TRIPS_architecture
Form of parallel computing
Bit-level parallelism is a form of parallel computing based on increasing processor word size. Increasing the word size reduces the number of instructions
Bit-level_parallelism
Type of low-level computer architecture
Maurice Wilkes wrote in 1995 that "Data flow stands apart as being the most radical of all approaches to parallelism and the one that has been least successful
Dataflow_architecture
Tse-yun Feng suggested the use of degree of parallelism to classify various computer architecture. It is based on sequential and parallel operations at
Feng's_classification
Computer programming language
runtime system for a stream programming language designed to leverage the parallelism of GPUs such as those from ATI or Nvidia. BrookGPU compiled programs
BrookGPU
Executing several computations during overlapping time periods
which can use parallelism or time-slicing to perform these tasks. Programs may exhibit parallelism only, concurrency only, both parallelism and concurrency
Concurrent_computing
GPU microarchitecture by Nvidia
area. Programmability aim was achieved with Kepler's Hyper-Q, Dynamic Parallelism and multiple new Compute Capabilities 3.x functionality. With it, higher
Kepler_(microarchitecture)
Division of the year
hours in a given region. On Earth, seasons are the result of the axial parallelism of Earth's tilted orbit around the Sun. In temperate and polar regions
Season
Computer expansion bus standard
utilizing internal parallelism offered by such devices. Enterprise-class SSDs can also implement SCSI over PCI Express. Certain data-center applications
PCI_Express
Representation of graph notation
optimizing compiler to make transformations to allow for parallelism. Dependency graph Control-flow graph Data-flow analysis Static program analysis Jeanne Ferrante;
Program_dependence_graph
Speed web pages are downloaded and displayed
instead of ordered and blocked can therefore use one connection for parallelism uses header compression to reduce overhead allows servers to "push" responses
Web_performance
Computer science professor
“3D parallelism” in modern artificial intelligence training that organizes data parallelism, pipeline parallelism, and operator/tensor parallelism into
Torsten_Hoefler
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