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CS 6120: Generating traces from LLVM - Cornell University
https://www.cs.cornell.edu/courses/cs6120/2019fa/blog/trace-gen-llvm/
A Tracing JIT Compiler for Erlang using LLVM - Lu
https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=5470892&fileOId=5470933
Tracing is a technique to augment an existing interpreter with a JIT simply by recording the instructions executed during a loop iteration, and then gener- ate optimized native code from this. Tracing compilers are particularly suited to optimize number crunching tight loops, an area where Erlang traditionally has been lacking.
A Tracing JIT Compiler for Erlang using LLVM | LUP …
https://lup.lub.lu.se/student-papers/search/publication/5470892
A Tracing JIT Compiler for Erlang using LLVM Mark Fänge, Johan LU ( 2015 ) In 1650-2884 EDA920 20102 Department of Computer Science Abstract We have modified the Erlang runtime to add support for a tracing just-in-time (JIT) …
BEAMJIT: An LLVM based just-in-time compiler for …
https://llvm.org/devmtg/2014-04/PDFs/Talks/drejhammar.pdf
Just-In-Time (JIT) Compilation as it Applies to BEAM Use light-weight pro ling to detect when we are at a place which is frequently executed. Trace the ow of execution until we get back to the same place. Compile trace to native code. NOTE: We are tracing the execution ow in the interpreter, the granularity is ner than BEAM opcodes.
GitHub - gligneul/FastLua: Lua trace JIT compiler using …
https://github.com/gligneul/FastLua
FastLua is an trace JIT compiler that works as an Lua (5.3) extension. There are only some minor modifications in the original interpreter. Currently, FastLua uses the LLVM toolchain to generate native code (there are plans to change the backend). For further information about Lua, see https://www.lua.org. ATENTION: This is still on development state.
Just-In-Time (JIT) Compiler with LLVM - Create Your Own …
https://createlang.rs/01_calculator/jit_intro.html
Just-In-Time (JIT) Compiler with LLVM. JIT compilation is a combination of Ahead-Of-Time (AOT) compilation and interpretation. As we saw previously, our Calc interpreter evaluates AST to values (actual integer i32 values) but a JIT compiler differs from an interpreter in what it outputs. Intuitively, JIT outputs are like AOT outputs but generated at runtime when traversing the AST. …
⚙ D76900 Enable IBT(Indirect Branch Tracking) in JIT with CET
https://reviews.llvm.org/D76900
There is already JIT tests in llvm unit test at /llvm/unittests/ExecutionEngine/, and some examples at llvm/example. This patch base on the build of llvm and libllvm. To test this patch, we need to build llvm self source code with CET enabled(-fcf-protection). JIT test mainly test runtime status (running fail/correct), not like lit test.
Tracing just-in-time compilation - Wikipedia
https://en.wikipedia.org/wiki/Tracing_just-in-time_compilation
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. This is opposed to traditional just-in-time (JIT) compilers that work on a per-method basis.
llvm/tools: lli REPL compared to LuaJIT - Stack Overflow
https://stackoverflow.com/questions/4055158/llvm-tools-lli-repl-compared-to-luajit
LuaJIT is a tracing JIT, which means it can re-optimize itself to better suite the data passed through the execution environment, however, LLVM is a static JIT, and thus will just generate the once-off best-case machine code for the corresponding source, which may leading it it loosing performance in tight loops or bad branch misspredictions.
LLVM Tutorial 1: A First Function
https://releases.llvm.org/2.6/docs/tutorial/JITTutorial1.html
LLVM Tutorial 1: A First Function. LLVM Tutorial 1: A First Function. For starters, let's consider a relatively straightforward function that takes three integer parameters and returns an arithmetic combination of them. This is nice and simple, especially since it involves no control flow: int mul_add (int x, int y, int z) { return x * y + z; }
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