졸업논문 기초조사서

2025. 09. 30. 화요일

UPMEM Hello World! Examplehttps://sdk.upmem.com/stable/02_HelloWorld.html Hello World! Example — UPMEM DPU SDK 2025.1.0 Documentation© Copyright 2015-2024, UPMEM SAS - All rights reserved.sdk.upmem.com 0. UPMEM SDK 설치하기 https://sdk.upmem.com UPMEM DPU SDKUPMEM SDK The Software Development Kit for programming and using the DPU provided by the UPMEM Acceleration platform.sdk.upmem.com tar -..

PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing Systemhttps://arxiv.org/abs/2502.15470 PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing SystemLarge language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies ..

Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Servinghttps://github.com/casys-kaist/pimba GitHub - casys-kaist/pimba: Official code repository for "Pimba: A Processing-in-Memory Acceleration for Post-Transformer LargeOfficial code repository for "Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Serving [MICRO'25]" - casys..

Accelerating LLMs using an Efficient GEMM Library and Target-Aware Optimizations on Real-World PIM Devices * TVM = deep learning compiler frameworkApache TVM is a machine learning compilation framework, following the principle of Python-first development and universal deployment. It takes in pre-trained machine learning models, compiles and generates deployable modules that can be embedded and..

2025. 05. 20. 화요일 Paper: https://open.library.ubc.ca/soa/cIRcle/collections/ubctheses/24/items/1.0435518 Offloading embedding lookups to processing-in-memory for deep learning recommender modelsRecommender systems are an essential part of many industries and businesses. Generating accurate recommendations is critical for user engagement and business revenue. Currently, deep learning recomme..

2025. 05. 13. PIM · TFLite 랩미팅 👩‍💻 📌 다음 시간까지 어떻게 나뉘어서 올라가는지 알고리즘 구현 조사하기https://open.library.ubc.ca/soa/cIRcle/collections/ubctheses/24/items/1.0435518 Offloading embedding lookups to processing-in-memory for deep learning recommender modelsAbstract Recommender systems are an essential part of many industries and businesses. Generating accurate recommendations is critical for user engagement..

2024. 10. 22 TuesdayVisualizatinon - Text memory + CPU Cycle    # Summary 정적으로 컴파일 된 코드 -> objdump로 확인 동적으로 연결 -> 코드 상에서 프린트 찍어서 확인 동적이냐 정적이냐 구분해서 분석하는 것 중요DLL이랑은 다른 내용 Rust 코드에서 print 구문으로 text 주소 확인하기 16진수 메모리 -> 100 단위도 매우 큰 scale csv 파일 -> Python으로 시각화 at Web - Plotly    https://plotly.com/python/ PlotlyPlotly'splotly.com  https://github.com/plotly/plotly.py GitHub - plotly/plotly.py: The in..

https://stackoverflow.com/questions/32026456/how-can-i-specify-an-area-of-code-to-instrument-it-by-pintool How can i specify an area of code to instrument it by pintool?There are four levels of granularity in Pin: routine, instruction and image, trace. Can i specify an limits/area to start and stop inserting instrumentation code. may by like directive like ( # startstackoverflow.com      # 자주 썼던..

PrIM BenchmarksVertor Addition Code Reivew https://github.com/SohyeonKim-dev/prim-benchmarks GitHub - SohyeonKim-dev/prim-benchmarks: PrIM (Processing-In-Memory benchmarks) is the first benchmark suite for a real-world prPrIM (Processing-In-Memory benchmarks) is the first benchmark suite for a real-world processing-in-memory (PIM) architecture. PrIM is developed to evaluate, analyze, and charact..