Llvlir - Low Level Variable Length Intermediate Representation

Related tags

Deep Learningllvlir
Overview

Low Level Variable Length Intermediate Representation

Low Level Variable Length Intermediate Representation is a succinct target independent byte-code for designed deferred translation modelling a VM designed to isolate an implementation of the C abstract virtual machine.

The following are some highlights of the LLVM and RISC-V inspired IR:

  • Lisp/SSA register VM with input registers encoded as deltas.
  • Fully parameterized operation type widths and vector sizes.
  • Support for signed and unsigned integer operations where necessary.
  • Sign or zero extension is explicit and is available for all widths.
  • Atomic memory order flags available on regular loads and stores.
  • Atomic support for compare and swap, lock and load, store conditional.
  • Supports mainstream bit manipulation operations (ctz, clz, popc, brev).
  • Vector SIMD with masked equivalents for all primitives except branches.
  • Vector SIMD conversions, sign or zero extension, truncation and merges.
  • Vector SIMD horizontal splat, lane shifts, rotates, and permutes (LUTs).
  • Vector SIMD parallel merge, pair reduce, swap, 2D/4D zip and unzip.
  • Vector SIMD double width multiply and cumulative sum.

LLVLIR Specification

Unofficial work in progress draft of the LLVLIR specification.

LLVLIR Build scripts

The specification contains machine readable reference tables that have been designed to aid automated generation of encoders and decoders. The reference tables can be extracted from the markdown specification.

Install python3 dependencies.

python3 -m pip install regex

Extract table of contents from the LLVLIR markdown.

./scripts/mdextract.py spec/llvlir.md 

Extract memory ordering flags from the LLVLIR markdown.

./scripts/mdextract.py --table memory-ordering-flags spec/llvlir.md

Create summary statistics on the operation table.

./scripts/stats.sh
Owner
Michael Clark
Michael Clark
TrTr: Visual Tracking with Transformer

TrTr: Visual Tracking with Transformer We propose a novel tracker network based on a powerful attention mechanism called Transformer encoder-decoder a

趙 漠居(Zhao, Moju) 66 Dec 27, 2022
A library built upon PyTorch for building embeddings on discrete event sequences using self-supervision

pytorch-lifestream a library built upon PyTorch for building embeddings on discrete event sequences using self-supervision. It can process terabyte-si

Dmitri Babaev 103 Dec 17, 2022
Transfer Learning Remote Sensing

Transfer_Learning_Remote_Sensing Simulation R codes for data generation and visualizations are in the folder simulation. Experiment: California Housin

2 Jun 21, 2022
Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX.

Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX. The repository combines a class agnostic object localizer to first detect the objects in the image

Ibai Gorordo 24 Nov 14, 2022
Node-level Graph Regression with Deep Gaussian Process Models

Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python

1 Jan 16, 2022
Resilience from Diversity: Population-based approach to harden models against adversarial attacks

Resilience from Diversity: Population-based approach to harden models against adversarial attacks Requirements To install requirements: pip install -r

0 Nov 23, 2021
PyTorch code for ICLR 2021 paper Unbiased Teacher for Semi-Supervised Object Detection

Unbiased Teacher for Semi-Supervised Object Detection This is the PyTorch implementation of our paper: Unbiased Teacher for Semi-Supervised Object Detection

Facebook Research 366 Dec 28, 2022
Self-Supervised Deep Blind Video Super-Resolution

Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base

Haoran Bai 35 Dec 09, 2022
DeepOBS: A Deep Learning Optimizer Benchmark Suite

DeepOBS - A Deep Learning Optimizer Benchmark Suite DeepOBS is a benchmarking suite that drastically simplifies, automates and improves the evaluation

Aaron Bahde 7 May 12, 2020
Code for ACL 2019 Paper: "COMET: Commonsense Transformers for Automatic Knowledge Graph Construction"

To run a generation experiment (either conceptnet or atomic), follow these instructions: First Steps First clone, the repo: git clone https://github.c

Antoine Bosselut 575 Jan 01, 2023
Character Controllers using Motion VAEs

Character Controllers using Motion VAEs This repo is the codebase for the SIGGRAPH 2020 paper with the title above. Please find the paper and demo at

Electronic Arts 165 Jan 03, 2023
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Generative Models Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine. Note: Gen

Agustinus Kristiadi 7k Jan 02, 2023
Repository for the paper "PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation", CVPR 2021.

PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation Code repository for the paper: PoseAug: A Differentiable Pose Augme

Pyjcsx 328 Dec 17, 2022
This is an easy python software which allows to sort images with faces by gender and after by age.

Gender-age Classifier This is an easy python software which allows to sort images with faces by gender and after by age. Usage First install Deepface

Claudio Ciccarone 6 Sep 17, 2022
Simple reference implementation of GraphSAGE.

Reference PyTorch GraphSAGE Implementation Author: William L. Hamilton Basic reference PyTorch implementation of GraphSAGE. This reference implementat

William L Hamilton 861 Jan 06, 2023
Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"

Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem

0 Dec 09, 2021
A flexible framework of neural networks for deep learning

Chainer: A deep learning framework Website | Docs | Install Guide | Tutorials (ja) | Examples (Official, External) | Concepts | ChainerX Forum (en, ja

Chainer 5.8k Jan 06, 2023
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

This is a playground for pytorch beginners, which contains predefined models on popular dataset. Currently we support mnist, svhn cifar10, cifar100 st

Aaron Chen 2.4k Dec 28, 2022
CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

CausalNLP CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable. Install pip install -U

Arun S. Maiya 95 Jan 03, 2023
Rotation Robust Descriptors

RoRD Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching Project Page | Paper link Evaluation and Datasets MMA : Training on

Udit Singh Parihar 25 Nov 15, 2022