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tracing just in time compilation wikipedia jump to content main menu main menu move to sidebar hide navigation main page contents current events random article about wikipedia contact us contribute help learn to edit community portal recent changes upload file special pages search search appearance donate create account log in personal tools donate create account log in contents move to sidebar hide top 1 overview 2 technical details toggle technical details subsection 2 1 profiling phase 2 2 tracing phase 2 3 optimization and code generation phase 2 4 execution 3 history 4 example of a trace 5 see also 6 references 7 external links toggle the table of contents tracing just in time compilation 4 languages فارسی 日本語 한국어 türkçe edit links article talk english read edit view history tools tools move to sidebar hide actions read edit view history general what links here related changes upload file permanent link page information cite this page get shortened url switch to legacy parser print export download as pdf printable version in other projects wikidata item appearance move to sidebar hide from wikipedia the free encyclopedia technique used to optimize the execution of a program at runtime program execution general concepts code translation compiler compile time optimizing compiler linking execution runtime system executable interpreter virtual machine intermediate representation ir types of code source code object code bytecode machine code microcode compilation strategies ahead of time aot just in time jit tracing just in time compile and go system precompilation transcompilation recompilation meta tracing notable runtimes android runtime art beam erlang common language runtime clr and mono cpython and pypy crt0 c target specific initializer java virtual machine jvm luajit objective c and swift s v8 and node js zend engine php notable compilers toolchains gnu compiler collection gcc llvm and clang msvc glasgow haskell compiler ghc v t e tracing just in time compilation is a technique used by virtual machines to optimize the execution of a program at runtime this is done by recording a linear sequence of frequently executed operations compiling them to native machine code and executing them in contrast traditional just in time compilation jit compiles each method in turn without optimizing between them overview edit just in time compilation is a technique to increase execution speed of programs by compiling parts of a program to machine code at runtime one way to categorize different jit compilers is by their compilation scope whereas method based jit compilers translate one method at a time to machine code tracing jits use frequently executed loops as their unit of compilation tracing jits are based on the behavior that many programs spend most of their time in some loops of the program termed hot loops and subsequent loop iterations often take similar paths virtual machines that have a tracing jit are often mixed mode execution environments meaning that they have either an interpreter or a method compiler along with the tracing jit technical details edit a tracing jit compiler goes through various phases at runtime first profiling information for loops is collected after a hot loop has been identified a special tracing phase is entered which records all executed operations of that loop this sequence of operations is called a trace the trace is then optimized and compiled to machine code when this loop is executed again the compiled trace is called instead of the program counterpart these steps are explained in detail in the following profiling phase edit the goal of profiling is to identify hot loops this is often done by counting the number of iterations for every loop after the count of a loop exceeds a certain threshold the loop is considered to be hot and tracing phase is entered tracing phase edit in the tracing phase the execution of the loop proceeds normally but in addition every executed operation is recorded into a trace the recorded operations are typically stored in a trace tree often in an intermediate representation ir tracing follows function calls which leads to them being inlined into the trace tracing continues until the loop reaches its end and jumps back to the start since the trace is recorded by following one concrete execution path of the loop later executions of that trace can diverge from that path to identify the places where that can happen special guard instructions are inserted into the trace one example for such a place are if statements the guard is a quick check to determine whether the original condition is still true if a guard fails the execution of the trace is aborted since tracing is done during execution the trace can be made to contain runtime information e g type information this information can later be used in the optimization phase to increase code efficiency optimization and code generation phase edit traces are easy to optimize since they represent only one execution path which means that no control flow exists and needs no handling typical optimizations include common subexpression elimination dead code elimination register allocation invariant code motion constant folding and escape analysis 1 after the optimization the trace is turned into machine code similarly to optimization this is easy due to the linear nature of traces execution edit after the trace has been compiled to machine code it can be executed in subsequent iterations of the loop trace execution continues until a guard fails history edit whereas the idea of jits reaches back to the 1960s tracing jits have become used more often only recently the first mention of an idea that is similar to today s idea of tracing jits was in 1970 2 it was observed that compiled code could be derived from an interpreter at runtime by simply storing the actions performed during interpretation the first implementation of tracing is dynamo a software dynamic optimization system that is capable of transparently improving the performance of a native instruction stream as it executes on the processor 3 to do this the native instruction stream is interpreted until a hot instruction sequence is found for this sequence an optimized version is generated cached and executed dynamo was later extended to dynamorio one dynamorio based project was a framework for interpreter construction that combines tracing and partial evaluation it was used to dynamically remove interpreter overhead from language implementations 4 in 2006 hotpathvm the first tracing jit compiler for a high level language citation needed was developed 5 this vm was capable of dynamically identifying frequently executed bytecode instructions which are traced and then compiled to machine code using static single assignment form ssa construction the motivation for hotpathvm was to have an efficient jvm for resource constrained mobile devices another example of a tracing jit is tracemonkey one of mozilla s javascript implementations for firefox 2009 6 tracemonkey compiles frequently executed loop traces in the dynamic language javascript at runtime and specializes the generated code for the actual dynamic types occurring on each path another project that utilizes tracing jits is pypy it enables the use of tracing jits for language implementations that were written with pypy s translation toolchain thus improving the performance of any program that is executed using that interpreter this is possible by tracing the interpreter itself instead of the program that is executed by the interpreter 7 tracing jits have also been explored by microsoft in the spur project for their common intermediate language cil spur is a generic tracer for cil which can also be used to trace through a javascript implementation 8 example of a trace edit consider the following python program that computes a sum of squares of successive whole numbers until that sum exceeds 100000 def square x return x x i 0 y 0 while true y square i if y 100000 break i i 1 a trace for this program could look something like this loopstart i1 y1 i2 int_mul i1 i1 i i y2 int_add y1 i2 y i i b1 int_gt y2 100000 guard_false b1 i3 int_add i1 1 i i 1 jump i3 y2 note how the function call to square is inlined into the trace and how the if statement is turned into a guard_false see also edit computer programming portal code generation compiler dalvik software hotspot virtual machine interpreter computing meta tracing profile guided optimization rpython semantic dictionary encoding references edit bolz carl friedrich cuni antonio fijabkowski maciej leuschel michael pedroni samuele rigo armin january 2011 allocation removal by partial evaluation in a tracing jit pdf proceedings of the 20th acm sigplan workshop on partial evaluation and program manipulation pepm 11 pp 43 52 doi 10 1145 1929501 1929508 s2cid 15871223 retrieved 2020 12 13 mitchell james g june 29 1970 the design and construction of flexible and efficient interactive programming systems phd carnegie mellon university isbn 978 0 8240 4414 5 lccn 79050563 oclc 633313022 s2cid 36249021 docket aai7104538 retrieved 2020 12 13 bala vasanth duesterwald evelyn banerjia sanjeev may 2000 dynamo a transparent dynamic optimization system pdf proceedings of the acm sigplan 2000 conference on programming language design and implementation pldi 00 pp 1 12 doi 10 1145 349299 349303 isbn 978 1 58113 199 4 s2cid 53223267 retrieved 2020 12 13 sullivan gregory t bruening derek l baron iris garnett timothy amarasinghe saman june 2003 dynamic native optimization of interpreters pdf proceedings of the 2003 workshop on interpreters virtual machines and emulators ivme 03 pp 50 57 citeseerx 10 1 1 14 9819 doi 10 1145 858570 858576 isbn 978 1 58113 655 5 s2cid 509405 retrieved 2020 12 13 cite conference cite uses deprecated parameter citeseerx help gal andreas probst christian w franz michael june 2006 hotpathvm an effective jit compiler for resource constrained devices pdf proceedings of the 2nd international conference on virtual execution environments vee 06 pp 144 153 doi 10 1145 1134760 1134780 isbn 978 1 59593 332 4 s2cid 17846788 wikidata q56580114 retrieved 2020 12 13 gal andreas orendorff jason ruderman jesse smith edwin w reitmaier rick bebenita michael chang mason franz michael eich brendan shaver mike anderson david mandelin david haghighat mohammad r kaplan blake hoare graydon zbarsky boris june 2009 trace based just in time type specialization for dynamic languages pdf proceedings of the 30th acm sigplan conference on programming language design and implementation pldi 09 pp 465 478 doi 10 1145 1542476 1542528 isbn 978 1 60558 392 1 s2cid 207172806 retrieved 2020 12 13 bolz carl friedrich cuni antonio fijalkowski maciej rigo armin july 2009 tracing the meta level pypy s tracing jit compiler pdf proceedings of the 4th workshop on the implementation compilation optimization of object oriented languages and programming systems icooolps 09 pp 18 25 doi 10 1145 1565824 1565827 isbn 978 1 60558 541 3 s2cid 7478596 retrieved 2020 12 13 bebenita michael brandner florian fahndrich manuel logozzo francesco schulte wolfram tillmann nikolai venter herman october 2010 spur a trace based jit compiler for cil pdf proceedings of the acm international conference on object oriented programming systems languages and applications oopsla 10 pp 708 725 doi 10 1145 1869459 1869517 isbn 978 1 4503 0203 6 s2cid 3395746 retrieved 2020 12 13 external links edit official website luajit retrieved from https en wikipedia org w index php title tracing_just in time_compilation oldid 1316709798 categories compiler construction software optimization hidden categories articles with short description short description matches wikidata cs1 errors deprecated parameters all articles with unsourced statements articles with unsourced statements from may 2018 official website not in wikidata articles with example python programming language code this page was last edited on 14 october 2025 at 02 08 utc page was rendered with parsoid text is available under the creative commons attribution sharealike 4 0 license additional terms may apply by using this site you agree to the terms of use and privacy policy wikipedia is a registered trademark of the wikimedia foundation inc a non profit organization privacy policy about wikipedia disclaimers contact wikipedia legal safety contacts code of conduct developers statistics cookie statement mobile view search search toggle the table of contents tracing just in time compilation 4 languages add topic