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블로그 다시 시작..

10-31

블로그 시작..

01-03

ElementryOS mouch pad Using it like a Mac Touch Gestures (Loki,Juno)

02-11

Logitech MX anywhere 2s 우분투에서 제스쳐 사용하기

02-11

ubuntu에서 parallel gzip사용하여 빠르게 압축하기(pigz)

02-11

Ubuntu pdf 를 이미지로 변환

02-11

ubuntu 16.04 python3 opencv 3.4 설치

02-11

jupyter notebook 다른python이 실행될 시

02-11

inplace_swap

02-11

ElementryOS mouch pad Using it like a Mac Touch Gestures (Loki,Juno)

02-11

docker tag 검색하기

02-11

docker 로 gitlab만들기

02-11

apt-get source 바꾸기

02-11

Linux ubuntu nvidia-docker 설치 및 자주 쓰는 명령어

01-08

Linux ubuntu Zsh 및 oh-my-zsh 설치

01-03

간단논문 정리 TVM An Automated End-to-End Optimizing Compiler for Deep Learning (OSDI 18)

02-12

논문 정리 LLVM A Compilation Framework for Lifelong Program Analysis & Transformation(CGO 04)

02-12

논문 정리 Chameleon Adaptive Code Optimization for Expedited Deep Neural Network Compilation(ICLR 2020)

02-12

논문 정리 NeuroVectorizer End-to-End Vectorization with Deep Reinforcement Learning (CGO 20)

02-12

간단논문 정리 Fast and Effective Orchestration of Compiler Optimizations(Zhelong Pan,Rudolf Eigenmann;Purdue University ;CGO’06)

02-12

간단논문 정리 End-to-End Deep Learning of Optimization Heuristics (PACT 17)

02-12

LLVM loop unroll and jam pass and view-cfg

02-12

LLVM (clang) build and install (ubuntu 18.04)

02-12

간단논문 정리 TVM An Automated End-to-End Optimizing Compiler for Deep Learning (OSDI 18)

02-12

논문 정리 Chameleon Adaptive Code Optimization for Expedited Deep Neural Network Compilation(ICLR 2020)

02-12

논문 정리 NeuroVectorizer End-to-End Vectorization with Deep Reinforcement Learning (CGO 20)

02-12

간단논문 정리 Fast and Effective Orchestration of Compiler Optimizations(Zhelong Pan,Rudolf Eigenmann;Purdue University ;CGO’06)

02-12

간단논문 정리 End-to-End Deep Learning of Optimization Heuristics (PACT 17)

02-12

간단논문 정리 DARTS DIFFERENTIABLE ARCHITECTURE SEARCH (ICLR 2019)

02-12

LLVM loop unroll and jam pass and view-cfg

02-12

간단논문 정리 DARTS DIFFERENTIABLE ARCHITECTURE SEARCH (ICLR 2019)

02-12

DUOATTENTION: EFFICIENT LONG-CONTEXT LLM INFERENCE WITH RETRIEVAL AND STREAMING HEADS

11-20

TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training

11-20

TIDALDECODE: FAST AND ACCURATE LLM DECOD ING WITH POSITION PERSISTENT SPARSE ATTENTION

11-20

SPARSEVLM: VISUAL TOKEN SPARSIFICATION FOR EFFICIENT VISION-LANGUAGE MODEL INFERENCE

11-20

SWIFTKV: FAST PREFILL-OPTIMIZED INFERENCE WITH KNOWLEDGE-PRESERVING MODEL TRANSFORMATION

11-20

Compression Strategy

11-20

A Systematic Study of Cross-Layer KV Sharing for Efficient LLM Inference

11-19

SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction

11-19

In-context KV-Cache Eviction for LLMs via Attention-Gate

11-19

Prompt Compression for Large Language Models: A Survey

11-19

Textbooks Are All You Need

11-19

Scaling Laws for Neural Language Models

11-19

Squeezed Attention: Accelerating Long Context Length LLM Inference

11-18

Recycled Attention: Efficient inference for long-context language models

11-18

TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection

11-18

VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration

11-18

MagicPIG: LSH Sampling for Efficient LLM Generation

11-18

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

11-14

Learning Transferable Visual Models From Natural Language Supervision

11-14

HART Efficient Visual Generation with Hybrid Autoregressive Transformer

11-14

Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

11-14

The CoT Collection Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning

11-14

VILA-U a Unified Foundation Model Integrating Visual Understanding and Generation

11-13

Condition-Aware Neural Network for Controlled Image Generation

11-13

DistriFusion Distributed Parallel Inference for High-Resolution Diffusion Models

11-13

VILA On Pre-training for Visual Language Models

11-13

FastComposer Tuning-Free Multi-Subject Image Generation with Localized Attention

11-13

ShadowKV KV Cache in Shadows for High-Throughput Long-Context LLM Inference

11-12

Query-Efficient Correlation Clustering with Noisy Oracle

11-12

LiteMoE Customizing On-device LLM Serving via Proxy Submodel Tuning

11-12

LaRS Latent Reasoning Skills for Chain-of-Thought Reasoning

11-12

Batch Calibration Rethinking Calibration for In-Context Learning and Prompt Engineering

11-12

Scientific Beta Multi-Beta Multi-Strategy Indices Implementing Multi-Factor Equity Portfolios with Smart Factor Indices

11-11

Foundations of Factor Investing

11-11

RAG4ITOps A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance

11-11

MagicPIG LSH Sampling for Efficient LLM Generation

11-11

EPIC Efficient Position-Independent Context Caching for Serving Large Language Models

11-11

ELICIT LLM Augmentation via External In-Context Capability

11-11

COMET Towards Partical W4A4KV4 LLMs Serving

11-11

The Cross-Section of Expected Stock Returns

11-10

Portfolio Selection

11-10

Capital asset prices A theory of market equilibrium under conditions of risk

11-10

MInference 1.0 Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

11-10

HYSYNTH Context-Free LLM Approximation for Guiding Program Synthesis

11-10

DynamoLLM Designing LLM Inference Clusters for Performance and Energy Efficiency

11-10

Can Graph Learning Improve Planning in LLM-based Agents?

11-10

ALPINE Unveiling the Planning Capability of Autoregressive Learning in Language Models

11-10

Transformers are Multi-State RNNs

11-07

Meta Large Language Model Compiler Foundation Models of Compiler Optimization

11-07

Enabling Tensor Language Model to Assist in Generating High-Performance Tensor Programs for Deep Learning

11-07

Efficient Streaming Language Models with Attention Sinks

11-07

Model Tells You What to Discard Adaptive KV Cache Compression for LLMs

11-07

BUZZ Beehive-structured Sparse KV Cache with Segmented Heavy Hitters for Efficient LLM Inference

11-06

KVSharer Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing

11-06

FLUX Fast Software-based Communication Overlap On GPUs Through Kernel Fusion

11-06

Don't Look Twice Faster Video Transformers with Run-Length Tokenization

11-06

CDMPP:ADevice-Model Agnostic Framework for Latency Prediction of Tensor Programs

11-06

Magicoder Empowering Code Generation with OSS-Instruct

11-05

SpotServe Serving Generative Large Language Models on Preemptible Instances

11-05

Optimal Kernel Orchestration for Tensor Programs with Korch

11-05

KernelGPT Enhanced Kernel Fuzzing via Large Language Models

11-05

Efficient Generative LLM Inference Using Phase Splitting

11-05

SpecExec Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices

11-04

Sequoia Scalable, Robust, and Hardware-aware Speculative Decoding

11-04

Memory Bounds for the Experts Problem

11-04

Helix Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs

11-04

GraphPipe Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism

11-04

Reasoning over Public and Private Data in Retrieval-Based Systems

11-03

MEGABYTE Predicting Million-byte Sequences with Multiscale Transformers

11-03

Reasoning over Public and Private Data in Retrieval-Based Systems

11-03

Breaking the Curse of Quality Saturation with User-Centric Ranking

11-03

Teola Towards End-to-End Optimization of LLM-based Applications

11-01

Quest Query-Aware Sparsity for Efficient Long-Context LLM Inference

11-01

What Matters in Transformers? Not All Attention is Needed Fusion

11-01

KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches

11-01

FlexGen High-Throughput Generative Inference of Large Language Models with a Single GPU

11-01

Prompt Cache Modular Attention Reuse for Low-Latency Inference

10-31

Better & Faster Large Language Models via Multi-token Prediction

10-31

Keyformer KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference

10-31

CacheBlend Fast Large Language Model Serving for RAG with Cached Knowledge Fusion

10-31

Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve

10-31

간단논문 정리 TVM An Automated End-to-End Optimizing Compiler for Deep Learning (OSDI 18)

02-12

논문 정리 LLVM A Compilation Framework for Lifelong Program Analysis & Transformation(CGO 04)

02-12

논문 정리 Chameleon Adaptive Code Optimization for Expedited Deep Neural Network Compilation(ICLR 2020)

02-12

논문 정리 NeuroVectorizer End-to-End Vectorization with Deep Reinforcement Learning (CGO 20)

02-12

간단논문 정리 Fast and Effective Orchestration of Compiler Optimizations(Zhelong Pan,Rudolf Eigenmann;Purdue University ;CGO’06)

02-12

간단논문 정리 End-to-End Deep Learning of Optimization Heuristics (PACT 17)

02-12

간단논문 정리 DARTS DIFFERENTIABLE ARCHITECTURE SEARCH (ICLR 2019)

02-12

자주쓰는 파이썬 스크립트 패턴

02-12

DUOATTENTION: EFFICIENT LONG-CONTEXT LLM INFERENCE WITH RETRIEVAL AND STREAMING HEADS

11-20

TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training

11-20

TIDALDECODE: FAST AND ACCURATE LLM DECOD ING WITH POSITION PERSISTENT SPARSE ATTENTION

11-20

SPARSEVLM: VISUAL TOKEN SPARSIFICATION FOR EFFICIENT VISION-LANGUAGE MODEL INFERENCE

11-20

SWIFTKV: FAST PREFILL-OPTIMIZED INFERENCE WITH KNOWLEDGE-PRESERVING MODEL TRANSFORMATION

11-20

Compression Strategy

11-20

A Systematic Study of Cross-Layer KV Sharing for Efficient LLM Inference

11-19

SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction

11-19

In-context KV-Cache Eviction for LLMs via Attention-Gate

11-19

Prompt Compression for Large Language Models: A Survey

11-19

Textbooks Are All You Need

11-19

Scaling Laws for Neural Language Models

11-19

Squeezed Attention: Accelerating Long Context Length LLM Inference

11-18

Recycled Attention: Efficient inference for long-context language models

11-18

TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection

11-18

VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration

11-18

MagicPIG: LSH Sampling for Efficient LLM Generation

11-18

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

11-14

Learning Transferable Visual Models From Natural Language Supervision

11-14

HART Efficient Visual Generation with Hybrid Autoregressive Transformer

11-14

Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

11-14

The CoT Collection Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning

11-14

VILA-U a Unified Foundation Model Integrating Visual Understanding and Generation

11-13

Condition-Aware Neural Network for Controlled Image Generation

11-13

DistriFusion Distributed Parallel Inference for High-Resolution Diffusion Models

11-13

VILA On Pre-training for Visual Language Models

11-13

FastComposer Tuning-Free Multi-Subject Image Generation with Localized Attention

11-13

ShadowKV KV Cache in Shadows for High-Throughput Long-Context LLM Inference

11-12

Query-Efficient Correlation Clustering with Noisy Oracle

11-12

LiteMoE Customizing On-device LLM Serving via Proxy Submodel Tuning

11-12

LaRS Latent Reasoning Skills for Chain-of-Thought Reasoning

11-12

Batch Calibration Rethinking Calibration for In-Context Learning and Prompt Engineering

11-12

Scientific Beta Multi-Beta Multi-Strategy Indices Implementing Multi-Factor Equity Portfolios with Smart Factor Indices

11-11

Foundations of Factor Investing

11-11

RAG4ITOps A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance

11-11

MagicPIG LSH Sampling for Efficient LLM Generation

11-11

EPIC Efficient Position-Independent Context Caching for Serving Large Language Models

11-11

ELICIT LLM Augmentation via External In-Context Capability

11-11

COMET Towards Partical W4A4KV4 LLMs Serving

11-11

The Cross-Section of Expected Stock Returns

11-10

Portfolio Selection

11-10

Capital asset prices A theory of market equilibrium under conditions of risk

11-10

MInference 1.0 Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

11-10

HYSYNTH Context-Free LLM Approximation for Guiding Program Synthesis

11-10

DynamoLLM Designing LLM Inference Clusters for Performance and Energy Efficiency

11-10

Can Graph Learning Improve Planning in LLM-based Agents?

11-10

ALPINE Unveiling the Planning Capability of Autoregressive Learning in Language Models

11-10

Transformers are Multi-State RNNs

11-07

Meta Large Language Model Compiler Foundation Models of Compiler Optimization

11-07

Enabling Tensor Language Model to Assist in Generating High-Performance Tensor Programs for Deep Learning

11-07

Efficient Streaming Language Models with Attention Sinks

11-07

Model Tells You What to Discard Adaptive KV Cache Compression for LLMs

11-07

BUZZ Beehive-structured Sparse KV Cache with Segmented Heavy Hitters for Efficient LLM Inference

11-06

KVSharer Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing

11-06

FLUX Fast Software-based Communication Overlap On GPUs Through Kernel Fusion

11-06

Don't Look Twice Faster Video Transformers with Run-Length Tokenization

11-06

CDMPP:ADevice-Model Agnostic Framework for Latency Prediction of Tensor Programs

11-06

Magicoder Empowering Code Generation with OSS-Instruct

11-05

SpotServe Serving Generative Large Language Models on Preemptible Instances

11-05

Optimal Kernel Orchestration for Tensor Programs with Korch

11-05

KernelGPT Enhanced Kernel Fuzzing via Large Language Models

11-05

Efficient Generative LLM Inference Using Phase Splitting

11-05

SpecExec Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices

11-04

Sequoia Scalable, Robust, and Hardware-aware Speculative Decoding

11-04

Memory Bounds for the Experts Problem

11-04

Helix Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs

11-04

GraphPipe Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism

11-04

Reasoning over Public and Private Data in Retrieval-Based Systems

11-03

MEGABYTE Predicting Million-byte Sequences with Multiscale Transformers

11-03

Reasoning over Public and Private Data in Retrieval-Based Systems

11-03

Breaking the Curse of Quality Saturation with User-Centric Ranking

11-03

Teola Towards End-to-End Optimization of LLM-based Applications

11-01

Quest Query-Aware Sparsity for Efficient Long-Context LLM Inference

11-01

What Matters in Transformers? Not All Attention is Needed Fusion

11-01

KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches

11-01

FlexGen High-Throughput Generative Inference of Large Language Models with a Single GPU

11-01

Prompt Cache Modular Attention Reuse for Low-Latency Inference

10-31

Better & Faster Large Language Models via Multi-token Prediction

10-31

Keyformer KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference

10-31

CacheBlend Fast Large Language Model Serving for RAG with Cached Knowledge Fusion

10-31

Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve

10-31

Scientific Beta Multi-Beta Multi-Strategy Indices Implementing Multi-Factor Equity Portfolios with Smart Factor Indices

11-11

Foundations of Factor Investing

11-11

The Cross-Section of Expected Stock Returns

11-10

Portfolio Selection

11-10

Capital asset prices A theory of market equilibrium under conditions of risk

11-10

Abseil Tip 65 제자리에 넣기

11-20

Abseil Tip 49 인자 기반 탐색

11-20

Abseil Tip 112 emplace vs. push_back

11-20

Abseil Tip 135 계약을 테스트하라, 구현을 테스트하지 마라

11-18

Abseil Tip 107 참조 수명 연장

11-18

Abseil Tip 101 반환 값, 참조 및 수명

11-18

Abseil Tip 86 클래스(enum class)를 활용한 열거형

11-14

Abseil Tip 77 임시 객체, 이동, 복사

11-14

Abseil Tip 64 Raw 문자열 리터럴

11-14

Abseil Tip 55 이름 개수 세기와 unique_ptr

11-13

Abseil Tip 122 테스트 픽스처, 명확성, 그리고 데이터 흐름

11-13

Abseil Tip 1 string_view의 활용 방법과 이점

11-12

Abseil Tip 65 제자리에 넣기

11-20

Abseil Tip 49 인자 기반 탐색

11-20

Abseil Tip 112 emplace vs. push_back

11-20

Abseil Tip 135 계약을 테스트하라, 구현을 테스트하지 마라

11-18

Abseil Tip 107 참조 수명 연장

11-18

Abseil Tip 101 반환 값, 참조 및 수명

11-18

Abseil Tip 86 클래스(enum class)를 활용한 열거형

11-14

Abseil Tip 77 임시 객체, 이동, 복사

11-14

Abseil Tip 64 Raw 문자열 리터럴

11-14

Abseil Tip 55 이름 개수 세기와 unique_ptr

11-13

Abseil Tip 122 테스트 픽스처, 명확성, 그리고 데이터 흐름

11-13

Abseil Tip 1 string_view의 활용 방법과 이점

11-12
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