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Increasing execution speed and reducing the overheads associated with loops
In compiler theory, loop optimization is the process of increasing execution speed and reducing the overheads associated with loops. It plays an important
Loop_optimization
Technique in computer software design
design, loop nest optimization (LNO) is an optimization technique that applies a set of loop transformations for the purpose of locality optimization or parallelization
Loop_nest_optimization
Compiler that optimizes generated code
equivalent code optimized for some aspect. Optimization is limited by a number of factors. Theoretical analysis indicates that some optimization problems are
Optimizing_compiler
Improving the efficiency of software
In computer science, program optimization, code optimization, or software optimization is the process of modifying a software system to make some aspect
Program_optimization
approaches to loop optimization, the set of the executions of the loop body is viewed as the set of integer points in a polyhedron defined by loop constraints
Integer points in convex polyhedra
Integer_points_in_convex_polyhedra
Loop transformation technique
Loop unrolling, also known as loop unwinding, is a loop transformation technique that attempts to optimize a program's execution speed at the expense of
Loop_unrolling
Process of developing trajectory performance
of constraints. Generally speaking, trajectory optimization is a technique for computing an open-loop solution to an optimal control problem. It is often
Trajectory_optimization
callee. Loop skewing: By "skewing" the logical shape of an array, this loop optimization can (when combined with loop interchange) eliminate loop-carried
Enabling_transformation
Framework for computer program optimization
loop programs are the typical, but not the only example, and the most common use of the model is for loop nest optimization in program optimization.
Polytope_model
Program function without side effects
side effects – allow for compiler optimization techniques such as common subexpression elimination and loop optimization similar to arithmetic operators
Pure_function
Test for determining the greatest common divisor
test) is the test used in study of loop optimization and loop dependence analysis to test the dependency between loop statements. A greatest common divisor
GCD_test
Type of compiler optimization
semantics of the program. Loop-invariant code motion (also called hoisting or scalar promotion) is a compiler optimization that performs this movement
Loop-invariant_code_motion
Compiler optimization
Loop fission (or loop distribution) is a compiler optimization in which a loop is broken into multiple loops over the same index range with each taking
Loop_fission_and_fusion
Graphical representation of a computer program or algorithm
There is now an infinite loop in the control flow graph, and the exit block can no longer be reached. Note that this optimization did not change the behavior
Control-flow_graph
Sequential model-based optimization of expensive black-box functions
Bayesian optimization is a sequential model-based strategy for global optimization of black-box objective functions whose evaluations are costly. It is
Bayesian_optimization
Control loop feedback mechanism
facilities no longer tune loops using the manual calculation methods shown above. Instead, PID tuning and loop optimization software are used to ensure
PID_controller
Control flow construct for executing code repeatedly
compiled to machine code, looping may be achieved using jumps; but some loops can be optimized to run without jumping. Usually, loops are expected to run for
Loop_(statement)
Series of actions for bettering effective usage
and/or efficiency. Process optimization is one of the major quantitative tools in industrial decision making. When optimizing a process, the goal is to
Process_optimization
technique of loop optimization was observed across several programming languages and compilers or interpreters. In some cases, a while loop with an inner
Inner_loop
Numeric value with an unclear meaning
most modern compilers will use techniques like constant folding and loop optimization to resolve the addition during compilation, so there is usually no
Magic_number_(programming)
Group of Fortran compilers
techniques for optimizing the compiled program: interprocedural optimization (IPO), profile-guided optimization (PGO), and other high-level optimizations (HLO)
Intel_Fortran_Compiler
Compiler
instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not
Intel_C++_Compiler
Free and open-source compiler for various programming languages
Link-time optimization Link-time optimization optimizes across object file boundaries to directly improve the linked binary. Link-time optimization relies
GNU_Compiler_Collection
Compiler optimization for conditionals in loops
Loop unswitching is a compiler optimization. It moves a conditional statement inside a loop outside by duplicating the loop's body and placing a version
Loop_unswitching
Compiler optimization technique
Loop splitting is a compiler optimization technique. It attempts to simplify a loop or eliminate dependencies by breaking it into multiple loops which
Loop_splitting
Generic term for compiler optimization
for performance and size benefits, and it is a common optimization performed in most optimizing compilers. Code motion has a variety of uses and benefits
Code_motion
Process where information about current status is used to influence future status
as inputs as part of a chain of cause and effect that forms a circuit or loop. The system can then be said to feed back into itself. The notion of cause-and-effect
Feedback
Case in parallel computing
inside loops. Automatic vectorization, like any loop optimization or other compile-time optimization, must exactly preserve program behavior. All dependencies
Automatic_vectorization
Invariants used to prove properties of loops
sorting, optimization, arithmetic etc.), characterizing each of them from the viewpoint of its invariant. Because of the similarity of loops and recursive
Loop_invariant
Computer program optimization method
substituted. The compiler will then try to optimize the result. Whole program optimization (WPO) is the compiler optimization of a program using information about
Interprocedural_optimization
Model-free reinforcement learning algorithm
Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient
Proximal_policy_optimization
Compiler optimization technique
profile-guided optimization (PGO, sometimes pronounced as pogo), also known as profile-directed feedback (PDF) or feedback-directed optimization (FDO), is
Profile-guided_optimization
Multiple names for the same data location
in Python 3 to enable this optimization. The Linux kernel does this because strict aliasing causes problems with optimization of inlined code. In such cases
Aliasing_(computing)
Russian mathematician (born 1956)
recognized expert in convex optimization, especially in the development of efficient algorithms and numerical optimization analysis. He is currently a
Yurii_Nesterov
Compiler transformation of sequential programs for parallel execution
parallelization, also auto-parallelization or autoparallelization, is a compiler optimization in which a compiler or other software tool transforms sequential program
Automatic_parallelization
in the GCC Graphite framework and in the LLVM Polly framework for loop optimizations. Free and open-source software portal Frameworks supporting the polyhedral
Integer_set_library
Graph representation in quantum mechanics
entanglement renormalization ansatz. Alternative formulations include loop optimization (loop-TNR), graph-independent local truncations (GILT), and the manifestly
Tensor_network
Optimization algorithm
Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate
Gradient_descent
Wearable machine meant to enhance a person's strength and mobility
Christopher G.; Collins, Steven H. (23 June 2017). "Human-in-the-loop optimization of exoskeleton assistance during walking". Science. 356 (6344): 1280–1284
Exoskeleton_(human)
Machine learning technique
function to improve an agent's policy through an optimization algorithm like proximal policy optimization. RLHF has applications in various domains in machine
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
to O5) along with any other optimization-related options, such as those for interprocedural analysis or loop optimizations. The XL compilers on AIX have
IBM_XL_C/C++_Compilers
Implementation of loop unrolling in C
is a way of manually implementing loop unrolling by interleaving two syntactic constructs of C: the do-while loop and a switch statement. Its discovery
Duff's_device
In computer science, a normalized loop (sometimes called well-behaved loop), is a loop in which the loop variable starts at 0 (or any constant) and gets
Normalized_loop
Degree to which disturbing a plasma system at equilibrium will destabilize it
for example, can help to maintain stability to tearing modes. Open-loop optimization of the pressure and current density profiles with external heating
Plasma_stability
Compiler optimization technique
the Smallest Program. The label "program optimization" has been given to a field that does not aspire to optimize but only to improve. This misnomer forced
Superoptimization
Compiler optimization
science, loop inversion is a compiler optimization and loop transformation in which a while loop is replaced by an if block containing a do..while loop. When
Loop_inversion
control problem as a mathematical optimization problem and then finds the controller that solves this optimization. H∞ techniques have the advantage over
H-infinity methods in control theory
H-infinity_methods_in_control_theory
Technique used to optimize the execution of a program at runtime
folding, and escape analysis. After the optimization, the trace is turned into machine code. Similarly to optimization, this is easy due to the linear nature
Tracing just-in-time compilation
Tracing_just-in-time_compilation
Particle Swarm Optimization and it is an array of values of a candidate solution of optimization problem. The cost function of the optimization problem determines
List of metaphor-based metaheuristics
List_of_metaphor-based_metaheuristics
Optimization algorithm
already been introduced, and was added to SGD optimization techniques in 1986. However, these optimization techniques assumed constant hyperparameters,
Stochastic_gradient_descent
Subroutine call performed as final action of a procedure
function is bypassed when the optimization is performed. For non-recursive function calls, this is usually an optimization that saves only a little time
Tail_call
j = j + 17; } This optimization is a special case of strength reduction. In some cases, it is possible to reverse this optimization in order to remove
Induction_variable
Competitive algorithm for searching a problem space
GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. In
Genetic_algorithm
Antenna constructions for different applications
transmitting loops Small transmitting loops are loop antennas whose perimeters are smaller than a half-wave, that have been specifically optimized for transmitting
Antenna_types
outer loop is called tile/block loop and the innermost loop is called element loop. Strip-mining was introduced for vector processors. It is a loop-transformation
Loop_sectioning
Type of radio antenna consisting of a loop or coil
A loop antenna is a radio antenna consisting of a loop or coil of wire, tubing, or other electrical conductor, that for transmitting is usually fed by
Loop_antenna
Program variable set but then not used
the loop repeatedly overwrites the same variable, so it can be reduced to only one call. Dead code Unreachable code "Insecure Compiler Optimization | OWASP"
Dead_store
How software progresses through its implementation
within the loop body that transfers control outside the loop. Early exit from a loop may be supported via a break statement. A loop inside the loop body of
Control_flow
Class of reinforcement learning algorithms
sub-class of policy optimization methods. Unlike value-based methods which learn a value function to derive a policy, policy optimization methods directly
Policy_gradient_method
Integrated development environment
elimination Interprocedural optimization analysis Loop optimizations Automatic parallelization Profile-guided optimization Scalar replacement Strength
Oracle_Developer_Studio
Optimization replacing a function call with that function's source code
subject to manual optimization or profile-guided optimization. This is a similar issue to other code expanding optimizations such as loop unrolling, which
Inline_expansion
Optimization algorithm
numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. As an example, ant colony optimization is a class
Ant colony optimization algorithms
Ant_colony_optimization_algorithms
Tools for optimizing binary code
hardware, while others lean heavily on profile-guided optimization and interprocedural optimization to deliver performance gains. Some utilize run-time
Binary_optimizer
Complexity class
NP-complete, often are optimization problems: Knapsack optimization problems Integer programming Travelling salesman optimization problem Maximum clique
NP-hardness
Technique in computer programming to optimize loop execution
In computer science, software pipelining is a technique used to optimize loops, in a manner that parallels hardware pipelining. Software pipelining is
Software_pipelining
create opportunities to further optimize, such as automatic vectorization of the array assignments. The major purpose of loop interchange is to take advantage
Loop_interchange
Mathematical optimization algorithms
Steihaug, also known as Hessian-free optimization, are a family of optimization algorithms designed for optimizing non-linear functions with large numbers
Truncated_Newton_method
design optimization is structural design optimization (SDO) is in building and construction sector. SDO emphasizes automating and optimizing structural
Design_optimization
function in the frequency domain; the resulting 'loop-shape' is then 'robustified' through optimization. Robustification usually has little effect at high
H-infinity_loop-shaping
JavaScript runtime environment
November 8, 2009. Node.js combined Google's V8 JavaScript engine, an event loop, and a low-level I/O API. In January 2010, a package manager was introduced
Node.js
Optimization algorithm
Limited-memory BFGS (L-BFGS or LM-BFGS) is an optimization algorithm in the collection of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno
Limited-memory_BFGS
Integrated development environment product
as a product in 1985. C 4.0 added optimizations and CodeView, a source-level debugger. C 5.0 added loop optimizations and huge memory model (arrays bigger
Microsoft_Visual_C++
American computer scientist and software engineer
in 1996, working under Craig Chambers on compilers and whole-program optimization techniques for object-oriented programming languages. He was elected
Jeff_Dean
Compiler optimization
In compiler construction, strength reduction is a compiler optimization where expensive operations are replaced with equivalent but less expensive operations
Strength_reduction
American chemical engineer (born 1966)
Harris, S.J.; Braatz, R.D.; Ermon, S.; Chueh, W.C. (2020), "Closed-loop optimization of fast-charging protocols for batteries with machine learning", Nature
Richard_D._Braatz
Problem optimization method
sub-problems. In the optimization literature, this relationship is called the Bellman equation. In terms of mathematical optimization, dynamic programming
Dynamic_programming
CPU Instruction
lock can be implemented with test-and-set, the test and test-and-set optimization lowers resource contention caused by bus locking, especially cache coherency
Test_and_test-and-set
Type of software bug
loop like on the right side. A function like the example above on the left would not be a problem in an environment supporting tail-call optimization;
Stack_overflow
Analysis in fluid dynamics
add the head losses around the loop in the direction of the loop; depending on whether the flow is with or against the loop, some pipes will have head losses
Pipe_network_analysis
Link from another website (referrer) to that web resource (referent)
method for Web authors Search engine optimization metrics – Collection, analysis, and reporting of web data to optimize search engines Website audit – Concept
Backlink
Software product
Search Optimization advocating the use of self-tuning schemes acting while a software system is running. Learning and Intelligent OptimizatioN refers
LIONsolver
In-band data value that must be handled specially by computer code
algorithm which uses its presence as a condition of termination, typically in a loop or recursive algorithm. The sentinel value is a form of in-band data that
Sentinel_value
NP-hard problem in combinatorial optimization
of the most intensively studied problems in optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally
Travelling_salesman_problem
Branch of engineering and mathematics
a means to achieve such a result, as it does not optimize a true performance index of the closed-loop control system. Together with PID controllers, MPC
Control_theory
used to guide loop transformation, it is generally acceptable to use a superset of the true dependencies—this can prevent an optimization but does not
Frameworks supporting the polyhedral model
Frameworks_supporting_the_polyhedral_model
System that manages the behavior of other systems
loop feedback mechanism Process control – Discipline that uses industrial control to achieve a production level of consistency Process optimization –
Control_system
Field of machine learning
policy optimization (PPO), to produce outputs that the reward model scores highly. The reward model substitutes for human raters during optimization, so
Reinforcement_learning
Optimization algorithm
In numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is an iterative algorithm
Hill_climbing
Mathematical algorithm
time, i.e., solving univariate (or at least much simpler) optimization problems in a loop. In the simplest case of cyclic coordinate descent, one cyclically
Coordinate_descent
system can be described using causal loop diagrams which may consist of balancing and reinforcing loops. Balancing loop is a structure representing negative
Escalation_archetype
Approach to controller design that explicitly deals with uncertainty
performance, and together are sought to be optimized by casting control design as a suitable optimization problem. The ability of feedback to cope with
Robust_control
Approximate nearest neighbor search algorithm
Evolution Controllability Graph drawing Social capital Link analysis Optimization Reciprocity Closure Homophily Transitivity Preferential attachment Balance
Hierarchical navigable small world
Hierarchical_navigable_small_world
American control theorist
ordinal optimization, including the book Perturbation Analysis of Discrete Event Dynamic Systems. and the book "Ordinal Optimization - Soft Optimization for
Yu-Chi_Ho
Use of functions that call themselves
for certain problems, algorithmic or compiler-optimization techniques such as tail call optimization may improve computational performance over a naive
Recursion_(computer_science)
Gradually typed dialect of Lua
upvalue optimization, and peephole optimization while preserving debugging information. Level 2 adds function inlining and loop unrolling. The bytecode uses
Luau_(programming_language)
dead code elimination alias analysis loop unrolling induction variable elimination loop-invariant code motion loop reversal Sunitha, K.V.N. (2013). Compiler
Vbcc
Sequence of operations for a task
Sollin are greedy algorithms that can solve this optimization problem. The heuristic method In optimization problems, heuristic algorithms find solutions
Algorithm
Evolutionary algorithm
strategy for numerical optimization. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex
CMA-ES
Overview of and topical guide to algorithms
Local search (optimization) Hill climbing Tabu search Genetic algorithm Ant colony optimization algorithms Particle swarm optimization Evolutionary algorithm
Outline_of_algorithms
to add an outer-level loop to handle the fuzziness (uncertainty). This outer-level loop comes down to solving an optimization problem. If the inner-level
Fuzzy_finite_element
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