jit

I'm interested in starting my own JIT project in C++. I'm not that unfamiliar with assembly, or compiler design etc etc. But, I am very unfamiliar with the resulting machine code format - like, what does a mov instruction actually look like when all is said and done and it's time to call that function pointer. So, what are the best resources for creating such a thing? Edit: Right now, I'm only interested in x86 on Windows, stretching a tiny bit to 64bit Windows in the future. You want to have a look at the processor manuals for the architecture you are interested in. Those manuals describe the

I'm using angular.io quickstart seed: https://angular.io/docs/ts/latest/guide/setup.html I'm using Angular4 with typescript JIT Currently I would like to add lodash so I can use this in my component and then do an npm run build e.g. tsc -p src/" and not get any errors My component: import { Component } from '@angular/core'; import * as _ from 'lodash'; @Component({ moduleId: module.id, selector: 'HomeComponent', templateUrl: 'home.component.html' }) export class HomeComponent { constructor() { console.log(_.last([1, 2, 3])); console.log('hello'); } } My systemjs.config: /** * System

I hear very conflicting information about Octave's experimental JIT compiler feature, ranging from "it was a toy project but it basically doesn't work" to "I've used it and I get a significant speedup". I'm aware that in order to use it successfully one needs to Compile octave with the --enable-jit at configure time Launch octave with the --jit-compiler option Specify jit compilation preference at runtime using jit_enable and jit_startcnt commands but I have been unable to reproduce the effects convincingly; not sure if this is because I've missed out any other steps I'm unaware of, or it

I am working on a JIT that uses LLVM. The language has a small run-time written in C++ which I compile down to LLVM IR using clang clang++ runtime.cu --cuda-gpu-arch=sm_50 -c -emit-llvm and then load the *.bc files, generate additional IR, and execute on the fly. The reason for the CUDA stuff is that I want to add some GPU acceleration to the runtime. However, this introduces CUDA specific external functions which gives errors such as: LLVM ERROR: Program used external function 'cudaSetupArgument' which could not be resolved! As discussed here , this is usually solved by including the