Liu Yanzhao (eqqlyz)

eqqlyz

Geek Repo

Company:IBM

Location:中国

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Liu Yanzhao's starred repositories

apint

Arbitrary precision integers library.

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GrainSet

Repository for our Nature Scientific Data paper: An annotated grain kernel image database for visual quality inspection.

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OpenCV-Cheatsheet

Sample code and examples for OpenCV, Python

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UVE2

UVE 2.0 Specification and tools

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gem5-avx

This adds partial support of AVX2 and AVX-512 to gem5.

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UVE

Unlimited Vector Extension with Data Streaming Support

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byrne-euclid

MetaPost + TeX rendition of Oliver Byrne's "The first six books of the Elements of Euclid"

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beebs

A set of benchmarks chosen to show the energy consumption of embedded devices under different conditions

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ncc

Neural Code Comprehension: A Learnable Representation of Code Semantics

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gpu-topk

Efficient Top-K implementation on the GPU

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parlaylib

A Toolkit for Programming Parallel Algorithms on Shared-Memory Multicore Machines

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XiangShan-doc

Documentation for XiangShan

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applegpuinfo

Print all known information about the GPU on Apple-designed chips

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metal-benchmarks

Apple GPU microarchitecture

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wp-theme

The WordPress theme boilerplate with a lot of useful features and helper functions

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scilab

Read only copy of https://gitlab.com/scilab/scilab

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NyuziProcessor

GPGPU microprocessor architecture

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torchtune

A Native-PyTorch Library for LLM Fine-tuning

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xls

XLS: Accelerated HW Synthesis

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llm.c

LLM training in simple, raw C/CUDA

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ChipAnnotationViewer

Chip die shot & annotation viewer

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gprofiler-performance-studio

The local version of the backend and UI for the gProfiler agent, featuring advanced flamegraph analysis tools. For the also free cloud version, please see https://profiler.granulate.io

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AI-Chip-List

A list of ICs and IPs for AI, Machine Learning and Deep Learning.

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Awesome-LLM-Inference

📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.

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cfc-demos

Demos for my talk CPU-Friendly Code

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