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{{Short description|Property of an intermediate representation in a compiler}}
In [[compiler]] design, '''static single assignment form''' (often abbreviated as '''SSA form''' or simply '''SSA''') is a
There are efficient algorithms for converting programs into SSA form. To convert to SSA, existing variables in the original IR are split into versions, new variables typically indicated by the original name with a subscript, so that every definition gets its own version. Additional statements that assign to new versions of variables may also need to be introduced at the join point of two control flow paths. Converting from SSA form to machine code is also efficient.
SSA makes numerous analyses needed for optimizations easier to perform, such as determining [[use-define chain]]s, because when looking at a use of a variable there is only one place where that variable may have received a value. Most optimizations can be adapted to preserve SSA form, so that one optimization can be performed after another with no additional analysis. The SSA based optimizations are usually more efficient and more powerful than their non-SSA form prior equivalents.
In [[functional language]] compilers, such as those for [[Scheme (programming language)|Scheme]] and [[ML programming language|ML]], [[continuation-passing style]] (CPS) is generally used. SSA is formally equivalent to a well-behaved subset of CPS excluding non-local control flow, so optimizations and transformations formulated in terms of one generally apply to the other. Using CPS as the intermediate representation is more natural for higher-order functions and interprocedural analysis. CPS also easily encodes [[call/cc]], whereas SSA does not.<ref name="Kelsey">{{cite book
|first1=Richard A. |last1=Kelsey
|title=Papers from the 1995 ACM SIGPLAN workshop on Intermediate representations |chapter=A correspondence between continuation passing style and static single assignment form |year=1995 |pages=13–22
|isbn=0897917545 |doi=10.1145/202529.202532 |s2cid=6207179 |chapter-url=https://
== History ==
SSA was developed in the 1980s by several researchers at [[International Business Machines|IBM]]
|title=Efficiently computing static single assignment form and the control dependence graph
|author1=Cytron, Ron |author2=Ferrante, Jeanne |author3=Rosen, Barry K. |author4=Wegman, Mark N. |author5=Zadeck, F. Kenneth |name-list-style=amp |journal=ACM Transactions on Programming Languages and Systems |volume=13 |year=1991 |pages=451–490 |url=http://www.cs.utexas.edu/~pingali/CS380C/2010/papers/ssaCytron.pdf |issue=4
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[[Compiler optimization]] algorithms that are either enabled or strongly enhanced by the use of SSA include:
* [[Constant
* [[Value range propagation]]<ref>[http://llvm.org/devmtg/2007-05/05-Lewycky-Predsimplify.pdf value range propagation]</ref> – precompute the potential ranges a calculation could be, allowing for the creation of branch predictions in advance
* [[Sparse conditional constant propagation]] – range-check some values, allowing tests to predict the most likely branch
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</pre>
Dominance frontiers define the points at which Φ functions are needed. In the above example, when control is passed to node 4, the definition of <code>result</code> used depends on whether control was passed from node 2 or 3. Φ functions are not needed for variables defined in a dominator, as there is only one possible definition that can apply.
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There is an efficient algorithm for finding dominance frontiers of each node. This algorithm was originally described in "Efficiently Computing Static Single Assignment Form and the Control Graph" by Ron Cytron, Jeanne Ferrante, et al. in 1991.<ref>{{cite journal |last1=Cytron |first1=Ron |last2=Ferrante |first2=Jeanne |last3=Rosen |first3=Barry K. |last4=Wegman |first4=Mark N. |last5=Zadeck |first5=F. Kenneth |title=Efficiently computing static single assignment form and the control dependence graph |journal=ACM Transactions on Programming Languages and Systems |date=1 October 1991 |volume=13 |issue=4 |pages=451–490 |doi=10.1145/115372.115320|s2cid=13243943 |doi-access=free }}</ref>
Keith D. Cooper, Timothy J. Harvey, and Ken Kennedy of [[Rice University]] describe an algorithm in their paper titled ''A Simple, Fast Dominance Algorithm'':<ref name="Cooper_2001">{{cite
|title=A Simple, Fast Dominance Algorithm |id=Rice University, CS Technical Report 06-33870
|
'''for each''' node b
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===Semi-pruned SSA===
Semi-pruned SSA form<ref>{{cite
Computing the set of block-local variables is a simpler and faster procedure than full live-variable analysis, making semi-pruned SSA form more efficient to compute than pruned SSA form. On the other hand, semi-pruned SSA form will contain more Φ functions.
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===Block arguments===
Block arguments are an alternative to Φ functions that is representationally identical but in practice can be more convenient during optimization. Blocks are named and take a list of block arguments, notated as function parameters. When calling a block the block arguments are bound to specified values. [[MLton]], [[Swift (programming language)|Swift
==Converting out of SSA form==
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{{excessive examples|section|date=August 2018}}
=== Open-source ===
* The ETH [[Oberon-2]] compiler was one of the first public projects to incorporate "GSA", a variant of SSA.▼
* [[WebKit]] uses SSA in its JIT compilers.<ref>{{Cite web|url=https://webkit.org/blog/3362/introducing-the-webkit-ftl-jit/|title=Introducing the WebKit FTL JIT|date=13 May 2014}}</ref><ref>{{Cite web|url=https://webkit.org/blog/5852/introducing-the-b3-jit-compiler/|title=Introducing the B3 JIT Compiler|date=15 February 2016}}</ref>▼
* [[Swift (programming language)|Swift]] defines its own SSA form above LLVM IR, called SIL (Swift Intermediate Language).<ref>{{Cite web|url=https://github.com/
* The [[Erlang (programming language)|Erlang]]
* The [[LLVM]] Compiler Infrastructure uses SSA form for all scalar register values (everything except memory) in its primary code representation. SSA form is only eliminated once register allocation occurs, late in the compile process (often at link time).
*
* The [[Open64]] compiler uses SSA form in its global scalar optimizer, though the code is brought into SSA form before and taken out of SSA form afterwards. Open64 uses extensions to SSA form to represent memory in SSA form as well as scalar values.▼
* [[Go (programming language)|Go]] (1.7: for x86-64 architecture only; 1.8: for all supported architectures).<ref>{{Cite web|url=https://golang.org/doc/go1.7#compiler|title=Go 1.7 Release Notes - The Go Programming Language|website=golang.org|access-date=2016-08-17}}</ref><ref>{{Cite web|url=https://golang.org/doc/go1.8#compiler|title=Go 1.8 Release Notes - The Go Programming Language|website=golang.org|access-date=2017-02-17}}</ref>▼
▲* Since the version 4 (released in April 2005) [[GNU Compiler Collection|GCC]], the [[GNU Compiler Collection]], makes extensive use of SSA. The [[front and back ends|frontends]] generate "[[GIMPLE#GENERIC and GIMPLE|GENERIC]]" code that is then converted into "[[GIMPLE#GENERIC and GIMPLE|GIMPLE]]" code by the "gimplifier". High-level optimizations are then applied on the SSA form of "GIMPLE". The resulting optimized intermediate code is then translated into [[Register Transfer Language|RTL]], on which low-level optimizations are applied. The architecture-specific [[Front and back ends|backend]]s finally turn RTL into [[assembly language]].
* [[IBM]]'s open source adaptive [[Java virtual machine]], [[Jikes RVM]], uses extended Array SSA, an extension of SSA that allows analysis of scalars, arrays, and object fields in a unified framework. Extended Array SSA analysis is only enabled at the maximum optimization level, which is applied to the most frequently executed portions of code.
* In 2002, [http://citeseer.ist.psu.edu/721276.html researchers modified] IBM's JikesRVM (named Jalapeño at the time) to run both standard Java [[bytecode]] and a typesafe SSA ([[SafeTSA]]) bytecode class files, and demonstrated significant performance benefits to using the SSA bytecode.▼
* [[Oracle Corporation|Oracle]]'s [[HotSpot (virtual machine)|HotSpot Java Virtual Machine]] uses an SSA-based intermediate language in its JIT compiler.<ref>{{cite web|url=http://www.oracle.com/technetwork/java/whitepaper-135217.html|publisher=Oracle Corporation|title=The Java HotSpot Performance Engine Architecture}}</ref>▼
* Microsoft [[Visual C++]] compiler backend available in [[Microsoft Visual Studio]] 2015 Update 3 uses SSA<ref>{{cite web|url=https://blogs.msdn.microsoft.com/vcblog/2016/05/04/new-code-optimizer|title=Introducing a new, advanced Visual C++ code optimizer|date=4 May 2016}}</ref>▼
▲* [[Mono (software)|Mono]] uses SSA in its JIT compiler called Mini.
* [http://jackcc.sf.net jackcc] is an open-source compiler for the academic instruction set Jackal 3.0. It uses a simple 3-operand code with SSA for its intermediate representation. As an interesting variant, it replaces Φ functions with a so-called SAME instruction, which instructs the register allocator to place the two live ranges into the same physical register.▼
* Although not a compiler, the [http://boomerang.sourceforge.net/ Boomerang] decompiler uses SSA form in its internal representation. SSA is used to simplify expression propagation, identifying parameters and returns, preservation analysis, and more.▼
* [[Portable.NET]] uses SSA in its JIT compiler.▼
* The Illinois Concert Compiler circa 1994<ref>{{cite web|url=http://www-csag.ucsd.edu/projects/concert.html|title=Illinois Concert Project|archive-url=https://web.archive.org/web/20140313140417/http://www-csag.ucsd.edu/projects/concert.html|archive-date=2014-03-13|url-status=dead}}</ref> used a variant of SSA called SSU (Static Single Use) which renames each variable when it is assigned a value, and in each conditional context in which that variable is used; essentially the static single information form mentioned above. The SSU form is documented in [http://www-csag.ucsd.edu/papers/jplevyak-thesis.ps John Plevyak's Ph.D Thesis].▼
* The COINS compiler uses SSA form optimizations as explained [https://web.archive.org/web/20040531024854/http://www.is.titech.ac.jp/~sassa/coins-www-ssa/english/ here].▼
* The [[Mozilla]] [[Firefox]] [[SpiderMonkey]] JavaScript engine uses SSA-based IR.<ref>{{cite web|url=https://wiki.mozilla.org/IonMonkey/Overview|title=IonMonkey Overview}},</ref>
* The [[Chromium (web browser)|Chromium]] [[V8 JavaScript engine]] implements SSA in its Crankshaft compiler infrastructure as [https://blog.chromium.org/2010/12/new-crankshaft-for-v8.html announced in December 2010]
* [[PyPy]] uses a linear SSA representation for traces in its JIT compiler.
* The [[Android Runtime]]<ref>{{cite video |title=The Evolution of ART - Google I/O 2016 |time=3m47s |url=https://www.youtube.com/watch?v=fwMM6g7wpQ8 |date=25 May 2016 |work=Google}}</ref> and the [[Dalvik (software)|Dalvik Virtual Machine]] use SSA.<ref>{{cite web |title=JIT through the ages |url=http://www.cs.columbia.edu/~aho/cs6998/reports/12-12-11_Ramanan_JIT.pdf |last=Ramanan |first=Neeraja | date=12 Dec 2011 }}</ref>
* The Standard ML compiler [[MLton]] uses SSA in one of its intermediate languages.
* [[LuaJIT]] makes heavy use of SSA-based optimizations.<ref>{{cite web|url=http://wiki.luajit.org/Optimizations|title=Bytecode Optimizations|publisher=the LuaJIT project}}</ref>
* The [[PHP]] and [[Hack (programming language)|Hack]] compiler [[HHVM]] uses SSA in its IR.<ref>{{cite web|url=https://github.com/facebook/hhvm/blob/master/hphp/doc/ir.specification|title=HipHop Intermediate Representation (HHIR)|website=[[GitHub]]|date=30 October 2021}}</ref>
*
* libFirm, a library for use as the [[Compiler#Three-stage compiler structure|middle and back ends of a compiler]], uses SSA form for all scalar register values until code generation by use of an SSA-aware register allocator.<ref>{{cite web|url=http://pp.ipd.kit.edu/firm/|title=Firm - Optimization and Machine Code Generation}}</ref>
▲* [[Go (programming language)|Go]] (1.7: for x86-64 architecture only; 1.8: for all supported architectures).<ref>{{Cite web|url=https://golang.org/doc/go1.7#compiler|title=Go 1.7 Release Notes - The Go Programming Language|website=golang.org|access-date=2016-08-17}}</ref><ref>{{Cite web|url=https://golang.org/doc/go1.8#compiler|title=Go 1.8 Release Notes - The Go Programming Language|website=golang.org|access-date=2017-02-17}}</ref>
* [[SPIR-V]], the shading language standard for the [[Vulkan (API)|Vulkan graphics API]] and [[compute kernel|kernel language]] for [[OpenCL]] compute API, is an SSA representation.<ref>{{cite web|url=https://www.khronos.org/registry/spir-v/specs/1.0/SPIRV.pdf|title=SPIR-V spec}}</ref>▼
* Various [[Mesa (computer graphics)|Mesa]] drivers via NIR, an SSA representation for shading languages.<ref>{{Cite web|url=https://lists.freedesktop.org/archives/mesa-dev/2014-December/072761.html|title=Reintroducing NIR, a new IR for mesa|last=Ekstrand|first=Jason|date=16 December 2014 }}</ref>
▲* [[WebKit]] uses SSA in its JIT compilers.<ref>{{Cite web|url=https://webkit.org/blog/3362/introducing-the-webkit-ftl-jit/|title=Introducing the WebKit FTL JIT|date=13 May 2014}}</ref><ref>{{Cite web|url=https://webkit.org/blog/5852/introducing-the-b3-jit-compiler/|title=Introducing the B3 JIT Compiler|date=15 February 2016}}</ref>
=== Commercial ===
▲* [[Swift (programming language)|Swift]] defines its own SSA form above LLVM IR, called SIL (Swift Intermediate Language).<ref>{{Cite web|url=https://github.com/apple/swift/blob/master/docs/SIL.rst|title=Swift Intermediate Language (GitHub)|website=[[GitHub]]|date=30 October 2021}}</ref><ref>{{Cite web|url=https://www.youtube.com/watch?v=Ntj8ab-5cvE |archive-url=https://ghostarchive.org/varchive/youtube/20211221/Ntj8ab-5cvE |archive-date=2021-12-21 |url-status=live|title=Swift's High-Level IR: A Case Study of Complementing LLVM IR with Language-Specific Optimization, LLVM Developers Meetup 10/2015|website=[[YouTube]]}}{{cbignore}}</ref>
▲* [[Erlang (programming language)|Erlang]] rewrote their compiler in OTP 22.0 to "internally use an intermediate representation based on Static Single Assignment (SSA)." With plans for further optimizations built on top of SSA in future releases.<ref>{{Cite web|url=http://www.erlang.org/news/132|title=OTP 22.0 Release Notes}}</ref>
▲* [[Oracle Corporation|Oracle]]'s [[HotSpot (virtual machine)|HotSpot Java Virtual Machine]] uses an SSA-based intermediate language in its JIT compiler.<ref>{{cite web|url=
▲* Microsoft [[Visual C++]] compiler backend available in [[Microsoft Visual Studio]] 2015 Update 3 uses SSA<ref>{{cite web|url=https://blogs.msdn.microsoft.com/vcblog/2016/05/04/new-code-optimizer|title=Introducing a new, advanced Visual C++ code optimizer|date=4 May 2016}}</ref>
▲* [[SPIR-V]], the shading language standard for the [[Vulkan (API)|Vulkan graphics API]] and [[compute kernel|kernel language]] for [[OpenCL]] compute API, is an SSA representation.<ref>{{cite web|url=https://www.khronos.org/registry/spir-v/specs/1.0/SPIRV.pdf|title=SPIR-V spec}}</ref>
* The IBM family of XL compilers, which include [[IBM XL C/C++ Compilers|C, C++]] and Fortran.<ref>{{cite journal|url=https://www.cs.rice.edu/~vs3/PDF/ibmjrd97.pdf|title=Automatic selection of high-order transformations in the IBM XL FORTRAN compilers|first=V.|last=Sarkar|journal=[[IBM Journal of Research and Development]]|volume=41|issue=3|pages=233–264|date=May 1997|publisher=IBM|doi=10.1147/rd.413.0233 }}</ref>
* NVIDIA [[CUDA]]<ref>{{cite journal|url=https://www.researchgate.net/publication/235605681|title=CUDA: Compiling and optimizing for a GPU platform|date=2012 |doi=10.1016/j.procs.2012.04.209 |last1=Chakrabarti |first1=Gautam |last2=Grover |first2=Vinod |last3=Aarts |first3=Bastiaan |last4=Kong |first4=Xiangyun |last5=Kudlur |first5=Manjunath |last6=Lin |first6=Yuan |last7=Marathe |first7=Jaydeep |last8=Murphy |first8=Mike |last9=Wang |first9=Jian-Zhong |journal=Procedia Computer Science |volume=9 |pages=1910–1919 |doi-access=free }}</ref>
=== Research and abandoned ===
▲* The ETH [[Oberon-2]] compiler was one of the first public projects to incorporate "GSA", a variant of SSA.
▲* The [[Open64]] compiler
▲* In 2002, [http://citeseer.ist.psu.edu/721276.html researchers modified] IBM's JikesRVM (named Jalapeño at the time) to run both standard Java [[bytecode]] and a typesafe SSA ([[SafeTSA]]) bytecode class files, and demonstrated significant performance benefits to using the SSA bytecode.
▲* [http://jackcc.sf.net jackcc] is an open-source compiler for the academic instruction set Jackal 3.0. It uses a simple 3-operand code with SSA for its intermediate representation. As an interesting variant, it replaces Φ functions with a so-called SAME instruction, which instructs the register allocator to place the two live ranges into the same physical register.
▲* The Illinois Concert Compiler circa 1994<ref>{{cite web|url=http://www-csag.ucsd.edu/projects/concert.html|title=Illinois Concert Project|archive-url=https://web.archive.org/web/20140313140417/http://www-csag.ucsd.edu/projects/concert.html|archive-date=2014-03-13|url-status=dead}}</ref> used a variant of SSA called SSU (Static Single Use) which renames each variable when it is assigned a value, and in each conditional context in which that variable is used; essentially the static single information form mentioned above. The SSU form is documented in [http://www-csag.ucsd.edu/papers/jplevyak-thesis.ps John Plevyak's Ph.D Thesis].
▲* The COINS compiler uses SSA form optimizations as explained [https://web.archive.org/web/20040531024854/http://www.is.titech.ac.jp/~sassa/coins-www-ssa/english/ here].
* Reservoir Labs' R-Stream compiler supports non-SSA (quad list), SSA and SSI (Static Single Information<ref>{{cite tech report |url=https://cscott.net/Publications/ssi.pdf |title=Static Single Information Form |last1=Ananian |first1=C. Scott |last2=Rinard |first2=Martin |year=1999|citeseerx = 10.1.1.1.9976}}</ref>) forms.<ref>{{cite book|url=https://www.springer.com/us/book/9780387097657|title=Encyclopedia of Parallel Computing}}</ref>
▲* Although not a compiler, the [
==References==
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