Reading list

All 28 required readings and 62 optional readings, by week. Links were individually verified against primary sources in August 2026. Back to the schedule.

Launch

Wk 01 · Sep 11 Course Introduction: AI as Workload, AI as Designer

Instructor-selected background

1. A New Golden Age for Computer Architecture CACM 2019
2. GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon arXiv 2026

Optional

• The Bitter Lesson (2019)
• Architecture 2.0: Why Computer Architects Need a Data-Centric AI Gymnasium (ACM SIGARCH Blog, 2023)

Computing for AI

Wk 02 · Sep 18 How to Study an AI Computing System + LLM Inference Fundamentals

Instructor-selected background

1. Roofline: An Insightful Visual Performance Model for Multicore Architectures CACM 2009
2. The Tail at Scale CACM 2013
3. FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness NeurIPS 2022

Optional

• MLPerf Inference Benchmark (ISCA 2020)
• Efficient Processing of Deep Neural Networks: A Tutorial and Survey (Proceedings of the IEEE 2017)

Computing for AI

Wk 03 · Sep 25 Serving Systems for LLMs and AI Agents

Student-led papers

1. Efficient Memory Management for Large Language Model Serving with PagedAttention SOSP 2023
   KV-cache virtualization, fragmentation, batching, vLLM
2. SGLang: Efficient Execution of Structured Language Model Programs NeurIPS 2024
   RadixAttention, KV reuse across program structure

Optional

• Splitwise: Efficient Generative LLM Inference Using Phase Splitting (ISCA 2024)
• Agentix: An Efficient Serving Engine for LLM Agents as General Programs (NSDI 2026)
• A Workflow-Aware Serving Layer for Agentic Applications (DyServe, arXiv 2026)
• DistServe: Disaggregating Prefill and Decoding for Goodput-Optimized Large Language Model Serving (OSDI 2024)
• Mooncake: A KVCache-Centric Disaggregated Architecture for LLM Serving (FAST 2025)
• Parrot: Efficient Serving of LLM-Based Applications with Semantic Variable (OSDI 2024)
• Fast Inference from Transformers via Speculative Decoding (ICML 2023)
• Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve (OSDI 2024)
• MemGPT: Towards LLMs as Operating Systems (2023)

Computing for AI

Wk 04 · Oct 2 AI Hardware: Accelerators and System-on-Chips

Student-led papers

1. In-Datacenter Performance Analysis of a Tensor Processing Unit ISCA 2017
   read as a ten-year retrospective
2. Agile SoC Development with Open ESP ICCAD 2020 project site
   Columbia's open-source heterogeneous SoC platform; available for course projects

Optional

• Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration (DAC 2021)
• TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings (ISCA 2023)
• Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks (ISCA 2016)
• Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach Using MAESTRO (MICRO 2019)
• Timeloop: A Systematic Approach to DNN Accelerator Evaluation (ISPASS 2019)
• NVIDIA H100 Tensor Core GPU Architecture (Whitepaper, 2022)
• NVIDIA Blackwell Architecture Technical Brief (2024)

Computing for AI

Wk 05 · Oct 9 Physical AI I: Inference Systems and Serving for Embodied AI

Student-led papers

1. Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots arXiv 2026
   deployable embodied-AI runtime across heterogeneous robots
2. VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference arXiv 2025
   overlapping inference with action execution; latency hiding
3. How Fast Can I Run My VLA? Demystifying VLA Inference Performance with VLA-Perf arXiv 2026
   analytical performance model; device/edge/cloud placement

Optional

• π0: A Vision-Language-Action Flow Model for General Robot Control (RSS 2025)
• OpenVLA: An Open-Source Vision-Language-Action Model (CoRL 2024)
• DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution (NeurIPS 2024)
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control (CoRL 2023)
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots (2025)
• Generative AI in Embodied Systems: System-Level Analysis of Performance, Efficiency and Scalability (ISPASS 2025)

Computing for AI

Wk 06 · Oct 16 Physical AI II: Hardware-Software Co-Design and Architecture

Student-led papers

1. DaDu-Corki: Algorithm-Architecture Co-Design for Embodied AI-Powered Robotic Manipulation ISCA 2025
   decoupling LLM inference from robotic control via trajectory prediction
2. ReCA: Integrated Acceleration for Real-Time and Efficient Cooperative Embodied Autonomous Agents ASPLOS 2025
   cross-layer co-design for cooperative embodied agents
3. Deltoris: Enabling Real-Time VLA Inference in Embodied AI via Bit-Level Sparsity and Speculative Inference MICRO 2026
   HW/SW co-design for diffusion-based VLA on edge devices

Optional

• Algorithm-Architecture Co-Design for Efficient VLA Inference via Speculative Inference and Verification (MICRO 2026)
• OctoCache: Caching Voxels for Accelerating 3D Occupancy Mapping in Autonomous Systems (ASPLOS 2025)
• RobotPerf: An Open-Source, Vendor-Agnostic, Benchmarking Suite for Evaluating Robotics Computing System Performance (ICRA 2024)
• DaDu Series: Fast and Efficient Robot Accelerators (ICCAD 2020)
• NVIDIA Jetson AGX Orin Series Technical Brief (2022)
• NVIDIA Jetson AGX Thor Developer Kit User Guide (2026)

Computing for AI

Wk 07 · Oct 23 Accelerating Neuro-Symbolic and Compositional AI

Student-led papers

1. CogSys: Efficient and Scalable Neurosymbolic Cognition System via Algorithm-Hardware Co-Design HPCA 2025
   workload characterization, reconfigurable processing
2. REASON: Accelerating Probabilistic Logical Reasoning for Scalable Neuro-Symbolic Intelligence HPCA 2026
   unified DAGs, irregular reasoning acceleration
3. Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming ASPLOS 2026
   compiling Datalog-based neurosymbolic programs to GPUs

Optional

• Scallop: A Language for Neurosymbolic Programming (PLDI 2023)
• DeepProbLog: Neural Probabilistic Logic Programming (NeurIPS 2018)
• NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI (DAC 2025)
• Towards Cognitive AI Systems: A Survey and Prospective on Neuro-Symbolic AI (ISPASS 2024)

AI for Computing

Wk 08 · Oct 30 AI for Software Systems: Compilers and GPU Kernels

Student-led papers

1. Faster Sorting Algorithms Discovered Using Deep Reinforcement Learning (AlphaDev) Nature 2023
   algorithm discovery, reward design, validation
2. AlphaEvolve: A Coding Agent for Scientific and Algorithmic Discovery DeepMind 2025
   evolutionary LLM code search across scheduling, TPU circuits, kernels
3. KernelBench: Can LLMs Write Efficient GPU Kernels? ICML 2025
   benchmark design; discussed with the Sakana AI CUDA Engineer episode

Optional

• CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research (CGO 2022)
• Large Language Models for Compiler Optimization (2023)
• Kevin: Multi-Turn RL for Generating CUDA Kernels (2025)
• Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization (Sakana AI, 2025)
• ECO: An LLM-Driven Efficient Code Optimizer for Warehouse Scale Computers (2025)

AI for Computing

Wk 10 · Nov 13 AI for Computer Architecture I: Measuring and Exploring

Student-led papers

1. ArchEval: Measuring AI Agents as Computer Architects arXiv 2026
   benchmarking LLM agents on architecture tasks
2. PF-LLM: Large Language Model Hinted Hardware Prefetching ASPLOS 2026
   AI inside the microarchitecture

Optional

• ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design (ISCA 2023)
• AgentDSE: Reasoning-Augmented Architectural Design Space Exploration (MLArchSys 2026)
• LLM-DSE: Searching Accelerator Parameters with LLM Agents (2025)
• ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators Using Reinforcement Learning (MICRO 2020)
• Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion (ISCA 2025)
• QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture (ICML 2026)
• Learning Memory Access Patterns (ICML 2018)

AI for Computing

Wk 11 · Nov 20 AI for Computer Architecture II: Agentic Design Systems

Student-led papers

1. CHIA: An Open-Source Framework for Principled, Agentic AI-Driven Hardware/Software Co-Design Research arXiv 2026
   composable design loops for agent-driven HW/SW co-design
2. Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization arXiv 2026
   LLM-driven microarchitecture evolution; seed quality bounds discovery

Optional

• ArchOrchestra: End-to-End Agentic Accelerator Design (forthcoming, 2026)
• AgentDSE: Reasoning-Augmented Architectural Design Space Exploration (MLArchSys 2026)
• LLM-DSE: Searching Accelerator Parameters with LLM Agents (2025)
• FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud (ISCA 2018)
• Chipyard: Integrated Design, Simulation, and Implementation Framework for Custom SoCs (IEEE Micro 2020)

AI for Computing

Wk 12 · Dec 4 AI for RTL and Chip Physical Design

Student-led papers

1. A Graph Placement Methodology for Fast Chip Design (AlphaChip) Nature 2021 (+2024 addendum) co-led by a pair companion critique
   read with Markov's 'The False Dawn' critique; co-led by a pair
2. ChipNeMo: Domain-Adapted LLMs for Chip Design NVIDIA 2024
   domain adaptation, retrieval, EDA scripts
3. Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification arXiv 2025
   RTL benchmarks and their limitations

Optional

• AssertLLM: Generating and Evaluating Hardware Verification Assertions from Design Specifications via Multi-LLMs (2024)
• Using LLMs to Facilitate Formal Verification of RTL (2023)
• DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement (DAC 2019)
• VerilogEval: Evaluating Large Language Models for Verilog Code Generation (ICCAD 2023)
• ChatEDA: A Large Language Model Powered Autonomous Agent for EDA (TCAD 2024)
• Automated Multi-Agent Workflows for RTL Design (VeriMaAS, 2025)
• SpecLLM: Exploring Generation and Review of VLSI Design Specification with Large Language Model (2024)
• Chip-Chat: Challenges and Opportunities in Conversational Hardware Design (MLCAD 2023)
• Redwood: A Frontier AI Accelerator Designed, Verified, and Deployed from Scratch in 2 Weeks by AI (2026)