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
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Extreme Classification 28 Dec 05, 2022
Deep Surface Reconstruction from Point Clouds with Visibility Information

Data, code and pretrained models for the paper Deep Surface Reconstruction from Point Clouds with Visibility Information.

Raphael Sulzer 23 Jan 04, 2023
Embracing Single Stride 3D Object Detector with Sparse Transformer

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

TuSimple 385 Dec 28, 2022
Open-AI's DALL-E for large scale training in mesh-tensorflow.

DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode

EleutherAI 432 Dec 16, 2022
Revisting Open World Object Detection

Revisting Open World Object Detection Installation See INSTALL.md. Dataset Our new data division is based on COCO2017. We divide the training set into

58 Dec 23, 2022
Context Axial Reverse Attention Network for Small Medical Objects Segmentation

CaraNet: Context Axial Reverse Attention Network for Small Medical Objects Segmentation This repository contains the implementation of a novel attenti

401 Dec 23, 2022
中文语音识别系列,读者可以借助它快速训练属于自己的中文语音识别模型,或直接使用预训练模型测试效果。

MASR中文语音识别(pytorch版) 开箱即用 自行训练 使用与训练分离(增量训练) 识别率高 说明:因为每个人电脑机器不同,而且有些安装包安装起来比较麻烦,强烈建议直接用我编译好的docker环境跑 目前docker基础环境为ubuntu-cuda10.1-cudnn7-pytorch1.6.

发送小信号 180 Dec 17, 2022
Generic ecosystem for feature extraction from aerial and satellite imagery

Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l

Mapbox 1.9k Jan 06, 2023
[NAACL & ACL 2021] SapBERT: Self-alignment pretraining for BERT.

SapBERT: Self-alignment pretraining for BERT This repo holds code for the SapBERT model presented in our NAACL 2021 paper: Self-Alignment Pretraining

Cambridge Language Technology Lab 104 Dec 07, 2022
Synthesizing and manipulating 2048x1024 images with conditional GANs

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

NVIDIA Corporation 6k Dec 27, 2022
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig

EMI-Group 175 Dec 30, 2022
Barlow Twins and HSIC

Barlow Twins and HSIC Unofficial Pytorch implementation for Barlow Twins and HSIC_SSL on small datasets (CIFAR10, STL10, and Tiny ImageNet). Correspon

Yao-Hung Hubert Tsai 49 Nov 24, 2022
Codes for paper "KNAS: Green Neural Architecture Search"

KNAS Codes for paper "KNAS: Green Neural Architecture Search" KNAS is a green (energy-efficient) Neural Architecture Search (NAS) approach. It contain

90 Dec 22, 2022
Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

NOTE: This is still being developed! Setup notes This document uses Jeff Sackmann's tennis data. You can obtain it as follows: git clone https://githu

Martin Ingram 1 Jan 20, 2022
Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

A Minimalist Approach to Offline Reinforcement Learning TD3+BC is a simple approach to offline RL where only two changes are made to TD3: (1) a weight

Scott Fujimoto 193 Dec 23, 2022
Hi Guys, here I am providing examples, which will help you in Lerarning Python

LearningPython Hi guys, here I am trying to include as many practice examples of Python Language, as i Myself learn, and hope these will help you in t

4 Feb 03, 2022
Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).

ALLINONE-Det ALLINONE-Det is a general and strong 3D object detection codebase built on OpenPCDet, which supports more methods, datasets and tools (de

Michael.CV 5 Nov 03, 2022
SIEM Logstash parsing for more than hundred technologies

LogIndexer Pipeline Logstash Parsing Configurations for Elastisearch SIEM and OpenDistro for Elasticsearch SIEM Why this project exists The overhead o

146 Dec 29, 2022
Ensembling Off-the-shelf Models for GAN Training

Data-Efficient GANs with DiffAugment project | paper | datasets | video | slides Generated using only 100 images of Obama, grumpy cats, pandas, the Br

MIT HAN Lab 1.2k Dec 26, 2022