Deeprecsys A System For Optimizing

Media Summary: To learn more about the latest research at the Harvard VLSI-Architecture group, please visit by Shijie Liu (NVIDIA Corporation), Nan Zheng (NVIDIA Corporation), Hui Kang (NVIDIA Corporation), Xavier Simmons (NVIDIA ... [2026 - DAY 2 - WORKSHOP] Sustainable prompt engineering is a challenge. Every time we change a model, update the ...

Deeprecsys A System For Optimizing - Detailed Analysis & Overview

To learn more about the latest research at the Harvard VLSI-Architecture group, please visit by Shijie Liu (NVIDIA Corporation), Nan Zheng (NVIDIA Corporation), Hui Kang (NVIDIA Corporation), Xavier Simmons (NVIDIA ... [2026 - DAY 2 - WORKSHOP] Sustainable prompt engineering is a challenge. Every time we change a model, update the ... Presented by Udit Gupta from Harvard University, online. ASPLOS'23: The 28th International Conference on Architectural Support for Programming Languages and Operating QCon San Francisco, the international software conference, returns November 17-21, 2025. Join senior software practitioners ...

ASPLOS'22: The 27th International Conference on Architectural Support for Programming Languages and Operating Lecture: Kirill Khrylchenko Seminar: Vladimir Baikalov This week we continue our journey through recommender Lecture: Kirill Khrylchenko Seminar: Artem Matveev In the first week of the course, we provide a gentle introduction to ... Ready to move beyond memory limits and scale your LLM fine-tuning? Join us for a webinar where ML and platform engineers ... Website Link: systemdrd.com Learn how to implement Fine-Tuned Domain Knowledge Augmentation using Retrieval-Augmented ...

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DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference (ISCA 2020)

A Hands On Tutorial Using DeepRecSys to Optimize At-Scale Neural Recommendation Inference

Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark

Cross-Stack Workload Characterization of Deep Recommendation Systems

Systematic LLM Prompt Optimization with DSPy and Databricks

[Alumni Talk] Designing Specialized Systems for Deep Learning-based Personalized Recommendation

ASPLOS'23 - Session 7B - Characterizing and Optimizing End-to-End Systems for Private Inference

Architectures That Scale Deep - Regaining Control in Deep Systems

ASPLOS'22 - Session 4A - RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale

DeepRecSys, лекция 2: ML дизайн рекомендательных систем

DeepRecSys Workshop 1: Metrics and Data

Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

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DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference (ISCA 2020)

DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference (ISCA 2020)

To learn more about the latest research at the Harvard VLSI-Architecture group, please visit https://vlsiarch.eecs.harvard.edu.

A Hands On Tutorial Using DeepRecSys to Optimize At-Scale Neural Recommendation Inference

A Hands On Tutorial Using DeepRecSys to Optimize At-Scale Neural Recommendation Inference

To learn more about the latest research at the Harvard VLSI-Architecture group, please visit https://vlsiarch.eecs.harvard.edu.

Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark

Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark

by Shijie Liu (NVIDIA Corporation), Nan Zheng (NVIDIA Corporation), Hui Kang (NVIDIA Corporation), Xavier Simmons (NVIDIA ...

Cross-Stack Workload Characterization of Deep Recommendation Systems

Cross-Stack Workload Characterization of Deep Recommendation Systems

To learn more about the latest research at the Harvard VLSI-Architecture group, please visit https://vlsiarch.eecs.harvard.edu.

Systematic LLM Prompt Optimization with DSPy and Databricks

Systematic LLM Prompt Optimization with DSPy and Databricks

[2026 - DAY 2 - WORKSHOP] Sustainable prompt engineering is a challenge. Every time we change a model, update the ...

[Alumni Talk] Designing Specialized Systems for Deep Learning-based Personalized Recommendation

[Alumni Talk] Designing Specialized Systems for Deep Learning-based Personalized Recommendation

Presented by Udit Gupta from Harvard University, online.

ASPLOS'23 - Session 7B - Characterizing and Optimizing End-to-End Systems for Private Inference

ASPLOS'23 - Session 7B - Characterizing and Optimizing End-to-End Systems for Private Inference

ASPLOS'23: The 28th International Conference on Architectural Support for Programming Languages and Operating

Architectures That Scale Deep - Regaining Control in Deep Systems

Architectures That Scale Deep - Regaining Control in Deep Systems

QCon San Francisco, the international software conference, returns November 17-21, 2025. Join senior software practitioners ...

ASPLOS'22 - Session 4A - RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale

ASPLOS'22 - Session 4A - RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale

ASPLOS'22: The 27th International Conference on Architectural Support for Programming Languages and Operating

DeepRecSys, лекция 2: ML дизайн рекомендательных систем

DeepRecSys, лекция 2: ML дизайн рекомендательных систем

Lecture: Kirill Khrylchenko Seminar: Vladimir Baikalov This week we continue our journey through recommender

DeepRecSys Workshop 1: Metrics and Data

DeepRecSys Workshop 1: Metrics and Data

Lecture: Kirill Khrylchenko Seminar: Artem Matveev In the first week of the course, we provide a gentle introduction to ...

Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

Ready to move beyond memory limits and scale your LLM fine-tuning? Join us for a webinar where ML and platform engineers ...

Implementing Fine-Tuned Domain Knowledge Augmentation using RAG.

Implementing Fine-Tuned Domain Knowledge Augmentation using RAG.

Website Link: systemdrd.com Learn how to implement Fine-Tuned Domain Knowledge Augmentation using Retrieval-Augmented ...