MIT Fast Code Seminar
Algorithms, Compilers, Accelerators, and Whatever It Takes


The MIT Fast Code Seminar is a seminar that covers the latest research topics in the theory and practice of performance engineering. Topics of interest include, but are not limited to, algorithm design and implementation; techniques for improving parallelism and locality; high-performance programming languages and frameworks; compilers for parallel code; tools for analyzing performance; hardware techniques for improving performance; parallel and concurrent data structures; models and algorithms for emerging technologies; high-performance solutions for databases, operating systems, networking, and artificial intelligence; and just plain clever hacks. To receive seminar announcements, please subscribe to this mailing list.

Spring 2024 Schedule

Tuesday 4/9/2024 2pmVahab MirrokniGoogle ResearchGraph Mining and Data Efficiency@Scale: From scalability to ML applications
Friday 4/19/2024 3pmMagdalen Dobson ManoharCarnegie Mellon UniversityParlayANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms
Friday 5/24/2024 2pmIke NassiUniversity of California-Santa Cruz Dynamic Adaptive Optimization: Recovering from Hardware Errors and Software Crashes in a Distributed Virtual Machine

Previous Seminars

Tuesday 12/5/2023 2pmNishil TalatiUniversity of MichiganHigh-Performance GPU Code Generation for Mining Motifs in Temporal Graphs
Tuesday 10/17/2023 2pmRohan YadavStanford UniversityDistributed Sparse Computing in Python
Thursday 5/11/2023Gal SelaTechnion - Israel Institute of TechnologySize Operation for Concurrent Data Structures
Thursday 4/20/2023Jialin LiNational University of SingaporeThe Case for Network Ordering in Distributed Systems Design
Wednesday 10/5/2022Rezaul ChowdhuryStony Brook UniversityFast Stencil Computations using FFT and Gaussian Approximations
Wednesday 9/28/2022Harsha SimhadriMicrosoft ResearchApproximate Nearest Neighbor Search algorithms for web-scale search and recommendation
Wednesday 9/14/2022David TenchRutgers University Dynamic Graph Connectivity: To Infinity And Beyond
Wednesday 6/1/2022 Hans VandierendonckQueen's University Belfast Memory Locality Optimisations for Graph Processing
Wednesday 4/20/2022Jessica ShiMIT Bridging Theory and Practice in Parallel Subgraph Computations
Wednesday 4/6/2022Neil ThompsonMIT How close are algorithms to being optimal?
Wednesday 2/16/2022William KuszmaulMIT Linear Probing Revisited: Tombstones Mark the Demise of Primary Clustering
Wednesday 12/8/2021Yuanhao WeiCMU Multi-point Queries on Concurrent Data Structures
Wednesday 11/17/2021Naama Ben-DavidVMware ResearchAlgorithms for Practical Distributed Agreement
Wednesday 11/3/2021Irene ZhangMicrosoft ResearchThe Demikernel Datapath OS Architecture for Microsecond-scale Datacenter Systems
Wednesday 10/13/2021Jan VitekNortheastern UniversityProductivity and Performance Reconciled: The Julia Story
Wednesday 5/12/2021Daniel LemireUniversity of QuebecParsing numbers at a gigabyte per second
Wednesday 4/28/2021Xuhao ChenMITSoftware and Hardware Systems for Emerging Graph Algorithms
Wednesday 4/7/2021Helen XuMIT Data Structure Design for Skewed Dynamic Graph Processing
Wednesday 3/31/2021Tim DavisTexas A&M SuiteSparse:GraphBLAS: graph algorithms in the language of sparse linear algebra
Wednesday 3/24/2021Martin Farach-ColtonRutgers University The Algorithmics of Address Translation
Wednesday 3/17/2021Maryam Mehri DehnaviUniversity of TorontoInspecting Irregular Computation Patterns to Generate Fast Code
Wednesday 3/10/2021Sam WestrickCMU Disentanglement: Provably Efficient Parallel Functional Programming (Slides)
Wednesday 2/24/2021Edgar SolomonikUIUCScalable Algorithms for Tensor Computations (Slides)
Monday 1/25/2021 Ariful AzadIndiana UniversityComputational Building Blocks for Machine Learning on Graphs (Slides)
Monday 1/11/2021Xuehai QianUSC High Performance Graph Mining Systems (Slides)
Monday 12/7/2020Yuanming HuMIT Taichi: A Language for High-Performance Computation on Spatially Sparse Data Structures
Monday 11/30/2020Scott BeamerUC Santa Cruz Efficiently Exploiting Low-Activity Factors to Accelerate RTL Simulation
Monday 11/9/2020Bradley KuszmaulGoogle Everyone Loves File: File Storage Service (FSS) in Oracle Cloud Infrastructure
Monday 11/2/2020Michael BenderStony Brook University Filters
Monday 10/26/2020Alex PothenPurdue University Approximation: A Paradigm for Designing Parallel Graph Algorithms
Monday 10/19/2020Rezaul ChowdhuryStony Brook University Automatic Derivation of Efficient Parallel Recursive Divide-&-Conquer Algorithms for Dynamic Programs
Monday 9/28/2020Michael MahoneyICSI and UC Berkeley ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Monday 9/21/2020Franz FranchettiCarnegie Mellon University SPIRAL's Operator Language: From Textbook Math to High Performance - With Correctness Guarantees
Monday 8/10/2020James DemmelUC Berkeley Communication-avoiding algorithms for linear algebra, machine learning and beyond
Monday 8/3/2020Kathy YelickUC Berkeley/
Lawrence Berkeley
National Lab
Genomic Analysis and Learning at Scale: Mapping Irregular Computations to Advanced Architectures
Monday 7/27/2020Larry Rudolph and
Steven Martin
Two Sigma Investments, LP/
QuickQuery: GPU-Based Approximate Query Processing for Sub-Second Exploration at Scale
Monday 7/20/2020Stephen ChouMIT Format Abstractions for Sparse Tensor Algebra Compilation
Monday 7/13/2020Michael Axtmann and
Peter Sanders
Karlsruhe Institute
of Technology
Engineering Scalable Parallel Sorting Algorithms
Monday 6/29/2020Umit CatalyurekGeorgia Tech Fast graph analytics on heterogenous and deep-memory architectures
Monday 6/22/2020Aydin BulucLawrence Berkeley
National Lab/UC Berkeley
Sparse Matrices Beyond Solvers: Graphs, Biology, and Machine Learning (Slides)
Monday 6/15/2020Wen-Mei HwuUIUC Fast GPU Code for Graphs (Slides)
Monday 6/8/2020David BaderNew Jersey Institute
of Technology
Solving Global Grand Challenges with High Performance Data Analytics
Monday 6/1/2020John OwensUC Davis Dynamic Data Structures on the GPU
Monday 5/11/2020Alex AikenStanford Program Optimization for Machine Learning
Monday 5/4/2020Ariya ShajiiMIT Seq: a high-performance language for bioinformatics
Monday 4/20/2020Neil Thompson
& Yash Sherry
MIT How fast are Algorithms Improving?
Tuesday 2/18/2020S. Tucker TaftAdaCore Safe Parallel Programming -- ParaSail, Ada 202X, OpenMP, and Rust
Monday 11/25/2019Bruce MaggsDuke University and
Emerald Innovations
A Speed-of-Light Internet Service Provider
Monday 11/18/2019Charith MendisMIT How to Modernize Compiler Technology
Monday 11/4/2019Yunming ZhangMIT GraphIt: A Domain-Specific Language for Writing High-Performance Graph Applications
Monday 10/21/2019Alex ConwayRutgers University SplinterDB: Closing the Bandwidth Gap on NVMe
Monday 9/30/2019Valentin ChuravyMIT Julia: Making dynamic programs run fast
Monday 9/23/2019Riyadh BaghdadiMIT Tiramisu: A Polyhedral Compiler for Dense and Sparse Deep Learning
Monday 9/16/2019Bill DallyNVIDIA Corporation and
Stanford University
Domain-Specific Accelerators
Tuesday 8/27/2019Laxman DhulipalaCarnegie Mellon University Algorithms and Systems for Processing Massive Static and Evolving Graphs
Tuesday 8/20/2019Tao B. SchardlMIT Tapir: Embedding Recursive Fork-Join Parallelism into LLVM's Intermediate Representation
Tuesday 8/6/2019Jeremy KepnerMIT Lincoln Laboratory
Supercomputing Center
Optimal system settings: How to not lose before you begin
Tuesday 7/30/2019I-Ting Angelina LeeWashington University
in St. Louis
Advances in Determinacy Race Detection for Task-Parallel Code
Tuesday 7/23/2019Maurice HerlihyBrown University Speculative Concurrency for Ethereum Smart Contracts
Tuesday 7/16/2019Song HanMIT AutoML for Efficiently Designing Efficient Neural Network Architectures
Tuesday 7/9/2019Fredrik KjolstadMIT The Sparse Tensor Algebra Compiler
Tuesday 6/11/2019Charles LeisersonMIT The Resurgence of Software Performance Engineering


Julian Shun (lead organizer)
Saman Amarasinghe
Adam Belay
Charles Leiserson
Tao B. Schardl