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cilka, cilkanol
Cilk, Cilk++ and Cilk Plus are general-purpose programming languages designed for multithreaded parallel computing They are based on the C and C++ programming languages, which they extend with constructs to express parallel loops and the fork–join idiom

Originally developed in the 1990s at the Massachusetts Institute of Technology MIT in the group of Charles E Leiserson, Cilk was later commercialized as Cilk++ by a spinoff company, Cilk Arts That company was subsequently acquired by Intel, which increased compatibility with existing C and C++ code, calling the result Cilk Plus


  • 1 History
    • 11 MIT Cilk
    • 12 Cilk Arts and Cilk++
    • 13 Intel Cilk Plus
    • 14 Differences between versions
  • 2 Language features
    • 21 Task parallelism:spawn and sync
    • 22 Inlets
    • 23 Parallel loops
    • 24 Reducers and hyperobjects
    • 25 Array notation
    • 26 Elemental functions
    • 27 #pragma simd
  • 3 Work-stealing
  • 4 See also
  • 5 References
  • 6 External links


MIT Cilkedit

The Cilk programming language grew out of three separate projects at the MIT Laboratory for Computer Science:2

  • Theoretical work on scheduling multi-threaded applications
  • StarTech – a parallel chess program built to run on the Thinking Machines Corporation's Connection Machine model CM-5
  • PCM/Threaded-C – a C-based package for scheduling continuation-passing-style threads on the CM-5

In April 1994 the three projects were combined and christened "Cilk" The name Cilk is not an acronym, but an allusion to "nice threads" silk and the C programming language The Cilk-1 compiler was released in September 1994

The original Cilk language was based on ANSI C, with the addition of Cilk-specific keywords to signal parallelism When the Cilk keywords are removed from Cilk source code, the result should always be a valid C program, called the serial elision or C elision of the full Cilk program, with the same semantics as the Cilk program running on a single processor Despite several similarities,which Cilk is not directly related to AT&T Bell Labs' Concurrent C

Cilk was implemented as a translator to C, targeting the GNU C Compiler GCC The last version, Cilk 546, is available from the MIT Computer Science and Artificial Intelligence Laboratory CSAIL, but is no longer supported3

A showcase for Cilk's capabilities was the Cilkchess parallel chess-playing program, which won several computer chess prizes in the 1990s, including the 1996 Open Dutch Computer Chess Championship4

Cilk Arts and Cilk++edit

Prior to c 2006, the market for Cilk was restricted to high-performance computing The emergence of multicore processors in mainstream computing means that hundreds of millions of new parallel computers are now being shipped every year Cilk Arts was formed to capitalize on that opportunity:in 2006, Leiserson launched Cilk Arts to create and bring to market a modern version of Cilk that supports the commercial needs of an upcoming generation of programmers The company closed a Series A venture financing round in October 2007, and its product, Cilk++ 10, shipped in December, 2008

Cilk++ differs from Cilk in several ways:support for C++, support for loops, and hyperobjects –a new construct designed to solve data race problems created by parallel accesses to global variables Cilk++ was proprietary software Like its predecessor, it was implemented as a Cilk-to-C++ compiler It supported the Microsoft and GNU compilers

Intel Cilk Plusedit

On July 31, 2009, Cilk Arts announced on its web site that its products and engineering team were now part of Intel Corp Intel and Cilk Arts integrated and advanced the technology further resulting in a September 2010 release of Intel Cilk Plus56 Cilk Plus adopts simplifications, proposed by Cilk Arts in Cilk++, to eliminate the need for several of the original Cilk keywords while adding the ability to spawn functions and to deal with variables involved in reduction operations Cilk Plus differs from Cilk and Cilk++ by adding array extensions, being incorporated in a commercial compiler from Intel, and compatibility with existing debuggers7

Cilk Plus was first implemented in the Intel C++ Compiler with the release of the Intel compiler in Intel Composer XE 2010citation needed An open source BSD-licensed implementation was contributed by Intel to the GNU Compiler Collection GCC, which shipped Cilk Plus support in version 49,8 except for the _Cilk_for keyword, which was added in GCC 50 In February 2013, Intel announced a Clang fork with Cilk Plus support9 The Intel Compiler, but not the open source implementations, comes with a race detector and a performance analyzer

Intel has stated its desire to refine Cilk Plus and to enable it to be implemented by other compilers to gain industry wide adoption10 It has also released a specification to enable other compatible implementations, and has said the trademark will be usable by compliant implementationscitation needed

Differences between versionsedit

In the original MIT Cilk implementation, the first Cilk keyword is in fact cilk, which identifies a function which is written in Cilk Since Cilk procedures can call C procedures directly, but C procedures cannot directly call or spawn Cilk procedures, this keyword is needed to distinguish Cilk code from C code Cilk Plus removes this restriction, as well as the cilk keyword, so C and C++ functions can call into Cilk Plus code and vice versa

Language featuresedit

The principle behind the design of the Cilk language is that the programmer should be responsible for exposing the parallelism, identifying elements that can safely be executed in parallel; it should then be left to the run-time environment, particularly the scheduler, to decide during execution how to actually divide the work between processors It is because these responsibilities are separated that a Cilk program can run without rewriting on any number of processors, including one

Task parallelism:spawn and syncedit

See also:Fork–join model

Cilk's main addition to C are two keywords that together allow writing task-parallel programs

  • The spawn keyword, when preceding a function call spawn fx, indicates that the function call fx can safely run in parallel with the statements following it in the calling function Note that the scheduler is not obligated to run this procedure in parallel; the keyword merely alerts the scheduler that it can do so
  • A sync statement indicates that execution of the current function cannot proceed until all previously spawned function calls have completed This is an example of a barrier method

In Cilk Plus, the keywords are spelled _Cilk_spawn and _Cilk_sync, or cilk_spawn and cilk_sync if the Cilk Plus headers are included

Below is a recursive implementation of the Fibonacci function in Cilk, with parallel recursive calls, which demonstrates the spawn, and sync keywords The original Cilk required any function using these to be annotated with the cilk keyword, which is gone as of Cilk Plus Cilk program code is not numbered; the numbers have been added only to make the discussion easier to follow

1 cilk int fibint n5 else 15

If this code was executed by a single processor to determine the value of fib2, that processor would create a frame for fib2, and execute lines 1 through 5 On line 6, it would create spaces in the frame to hold the values of x and y On line 8, the processor would have to suspend the current frame, create a new frame to execute the procedure fib1, execute the code of that frame until reaching a return statement, and then resume the fib2 frame with the value of fib1 placed into fib2's x variable On the next line, it would need to suspend again to execute fib0 and place the result in fib2's y variable

When the code is executed on a multiprocessor machine, however, execution proceeds differently One processor starts the execution of fib2; when it reaches line 8, however, the spawn keyword modifying the call to fibn-1 tells the processor that it can safely give the job to a second processor:this second processor can create a frame for fib1, execute its code, and store its result in fib2's frame when it finishes; the first processor continues executing the code of fib2 at the same time A processor is not obligated to assign a spawned procedure elsewhere; if the machine only has two processors and the second is still busy on fib1 when the processor executing fib2 gets to the procedure call, the first processor will suspend fib2 and execute fib0 itself, as it would if it were the only processor Of course, if another processor is available, then it will be called into service, and all three processors would be executing separate frames simultaneously

The preceding description is not entirely accurate Even though the common terminology for discussing Cilk refers to processors making the decision to spawn off work to other processors, it is actually the scheduler which assigns procedures to processors for execution, using a policy called work-stealing, described later

If the processor executing fib2 were to execute line 13 before both of the other processors had completed their frames, it would generate an incorrect result or an error; fib2 would be trying to add the values stored in x and y, but one or both of those values would be missing This is the purpose of the sync keyword, which we see in line 11:it tells the processor executing a frame that it must suspend its own execution until all the procedure calls it has spawned off have returned When fib2 is allowed to proceed past the sync statement in line 11, it can only be because fib1 and fib0 have completed and placed their results in x and y, making it safe to perform calculations on those results

The code example above uses the syntax of Cilk-5 The original Cilk Cilk-1 used a rather different syntax that required programming in an explicit continuation-passing style, and the Fibonacci examples looks as follows:11

thread fibcont int k, int nelse thread sumcont int k, int x, int y

Inside fib's recursive case, the spawn_next keyword indicates the creation of a successor thread as opposed to the child threads created by spawn, which executes the sum subroutine after waiting for the continuation variables x and y to be filled in by the recursive calls The base case and sum use a send_argumentk, n operation to set their continuation variable k to the value of n, effectively "returning" the value to the successor thread


The two remaining Cilk keywords are slightly more advanced, and concern the use of inlets Ordinarily, when a Cilk procedure is spawned, it can return its results to the parent procedure only by putting those results in a variable in the parent's frame, as we assigned the results of our spawned procedure calls in the example to x and y

The alternative is to use an inlet An inlet is a function internal to a Cilk procedure which handles the results of a spawned procedure call as they return One major reason to use inlets is that all the inlets of a procedure are guaranteed to operate atomically with regards to each other and to the parent procedure, thus avoiding the bugs that could occur if the multiple returning procedures tried to update the same variables in the parent frame at the same time

  • The inlet keyword identifies a function defined within the procedure as an inlet
  • The abort keyword can only be used inside an inlet; it tells the scheduler that any other procedures that have been spawned off by the parent procedure can safely be aborted

Inlets were removed when Cilk became Cilk++, and are not present in Cilk Plus

Parallel loopsedit

Cilk++ added an additional construct, the parallel loop, denoted cilk_for in Cilk Plus These loops look like

1 void loopint a, int n2 7

This implements the parallel map idiom:the body of the loop, here a call to f followed by an assignment to the array a, is executed for each value of i from zero to n in an indeterminate order The optional "grain size" pragma determines the coarsening:any sub-array of one hundred or fewer elements is processed sequentially Although the Cilk specification does not specify the exact behavior of the construct, the typical implementation is a divide-and-conquer recursion,12 as if the programmer had written

static void recursionint a, int start, int endelse void loopint a, int n

The reasons for generating a divide-and-conquer program rather than the obvious alternative, a loop that spawn-calls the loop body as a function, lie in both the grainsize handling and in efficiency:doing all the spawning in a single task makes load balancing a bottleneck13

A review of various parallel loop constructs on HPCwire found the cilk_for construct to be quite general, but noted that the Cilk Plus specification did not stipulate that its iterations need to be data-independent, so a compiler cannot automatically vectorize a cilk_for loop The review also noted the fact that reductions eg, sums over arrays need additional code12

Reducers and hyperobjectsedit

Cilk++ added a kind of objects called hyperobjects, that allow multiple strands to share state without race conditions and without using explicit locks Each strand has a view on the hyperobject that it can use and update; when the strands synchronize, the views are combined in a way specified by the programmer14

The most common type of hyperobject is a reducer, which corresponds to the reduction clause in OpenMP or to the algebraic notion of a monoid Each reducer has an identity element and an associative operation that combines two values The archetypal reducer is summation of numbers:the identity element is zero, and the associative reduce operation computes a sum This reducer is built into Cilk++ and Cilk Plus:

// Compute ∑ fooi for i from 0 to N, in parallelcilk::reducer_opadd<float> result0;cilk_for int i = 0; i < N; i++result += fooi;

Other reducers can be used to construct linked lists or strings, and programmers can define custom reducers

A limitation of hyperobjects is that they provide only limited determinacy Burckhardt et al point out that even the sum reducer can result in non-deterministic behavior, showing a program that may produce either 1 or 2 depending on the scheduling order:15

void add1cilk::reducer_opadd<int> &r // cilk::reducer_opadd<int> r0;cilk_spawn add1r;if r == 0 cilk_sync;outputrget_value;

Array notationedit

Intel Cilk Plus adds notation to express high-level operations on entire arrays or sections of arrays; eg, an axpy-style function that is ordinarily written

// y ← α x + y void axpyint n, float alpha, const float x, float y

can in Cilk Plus be expressed as

y0:n += alphax0:n;

This notation helps the compiler to effectively vectorize the application Intel Cilk Plus allows C/C++ operations to be applied to multiple array elements in parallel, and also provides a set of built-in functions that can be used to perform vectorized shifts, rotates, and reductions Similar functionality exists in Fortran 90; Cilk Plus differs in that it never allocates temporary arrays, so memory usage is easier to predict

Elemental functionsedit

In Cilk Plus, an elemental function is a regular function which can be invoked either on scalar arguments or on array elements in parallel They are similar to the kernel functions of OpenCL

#pragma simdedit

This pragma gives the compiler permission to vectorize a loop even in cases where auto-vectorization might fail It is the simplest way to manually apply vectorization


Main article:Work stealing

The Cilk scheduler uses a policy called "work-stealing" to divide procedure execution efficiently among multiple processors Again, it is easiest to understand if we look first at how Cilk code is executed on a single-processor machine

The processor maintains a stack on which it places each frame that it has to suspend in order to handle a procedure call If it is executing fib2, and encounters a recursive call to fib1, it will save fib2's state, including its variables and where the code suspended execution, and put that state on the stack It will not take a suspended state off the stack and resume execution until the procedure call that caused the suspension, and any procedures called in turn by that procedure, have all been fully executed

With multiple processors, things of course change Each processor still has a stack for storing frames whose execution has been suspended; however, these stacks are more like deques, in that suspended states can be removed from either end A processor can still only remove states from its own stack from the same end that it puts them on; however, any processor which is not currently working having finished its own work, or not yet having been assigned any will pick another processor at random, through the scheduler, and try to "steal" work from the opposite end of their stack –suspended states, which the stealing processor can then begin to execute The states which get stolen are the states that the processor stolen from would get around to executing last

See alsoedit

  • Grand Central Dispatch
  • Intel Concurrent Collections CnC
  • Intel Parallel Building Blocks PBB
    • Intel Array Building Blocks ArBB
  • Intel Parallel Studio
  • NESL
  • OpenMP
  • Parallel computing
  • Sieve C++ Parallel Programming System
  • Threading Building Blocks TBB
  • Unified Parallel C


  1. ^ LaGrone, James; Aribuki, Ayodunni; Addison, Cody; Chapman, Barbara 2011 A Runtime Implementation of OpenMP Tasks 7th Int'l Workshop on OpenMP pp 165–178 CiteSeerX 10112212775 doi:101007/978-3-642-21487-5_13 
  2. ^ "A Brief History of Cilk
  3. ^ "The Cilk Project" MIT CSAIL 8 October 2010 Retrieved 25 January 2016 
  4. ^ Leiserson, Charles E; Plaat, Aske 1998 "Programming parallel applications in Cilk" PDF SIAM News 31 
  5. ^ "Intel Flexes Parallel Programming Muscles", HPCwire 2010-09-02 Retrieved on 2010-09-14
  6. ^ "Parallel Studio 2011:Now We Know What Happened to Ct, Cilk++, and RapidMind", Dr Dobbs Journal 2010-09-02 Retrieved on 2010-09-14
  7. ^ "Intel Cilk Plus:A quick, easy and reliable way to improve threaded performance", Intel Retrieved on 2010-09-14
  8. ^ "GCC 49 Release Series Changes, New Features, and Fixes", Free Software Foundation, Inc Retrieved on 2014-06-29
  9. ^ Cilk Plus/LLVM
  10. ^ "Cilk Plus specification and runtime ABI freely available for download", James Reinders Retrieved on 2010-11-03
  11. ^ Blumofe, Robert D; Joerg, Christopher F; Kuszmaul, Bradley C; Leiserson, Charles E; Randall, Keith H; Zhou, Yuli 1995 Cilk:An Efficient Multithreaded Runtime System PDF Proc ACM SIGPLAN Symp Principles and Practice of Parallel Programming pp 207–216 
  12. ^ a b Wolfe, Michael 6 April 2015 "Compilers and More:The Past, Present and Future of Parallel Loops" HPCwire 
  13. ^ McCool, Michael; Reinders, James; Robison, Arch 2013 Structured Parallel Programming:Patterns for Efficient Computation Elsevier p 30 
  14. ^ Frigo, Matteo; Halpern, Pablo; Leiserson, Charles E; Lewin-Berlin, Stephen 2009 Reducers and other Cilk++ hyperobjects PDF Proc Annual Symposium on Parallelism in Algorithms and Architectures SPAA ACM 
  15. ^ Burckhardt, Sebastian; Baldassin, Alexandro; Leijen, Daan 2010 Concurrent Programming with Revisions and Isolation Types PDF Proc OOPSLA/SPLASH 

External linksedit

  • Official website for Cilk Plus
  • Cilk Project website at MIT
  • Arch D Robison, "Cilk Plus:Language Support for Thread and Vector Parallelism" and "Parallel Programming with Cilk Plus", July 16, 2012

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