The Fastcode Seminar covers the latest research topics in the theory, practice, and teaching 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.
Mon Apr 14, 2025
Saman Amarasinghe,
MIT
Wed Feb 19, 2025
Yihan Sun,
University of California-Riverside
Scalable Parallel Algorithms
Tue Feb 4, 2025
Asaf Cidon,
Columbia University
Customizing the OS Storage and Memory Stacks with eBPF
Fri May 24, 2024
Ike Nassi,
University of California-Santa Cruz
Dynamic Adaptive Optimization—Recovering from Hardware Errors and Software Crashes in a Distributed Virtual Machine
Fri Apr 19, 2024
Magdalen Dobson Manohar,
Carnegie Mellon University
ParlayANN—Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms
Tue Apr 9, 2024
Vahab Mirrokni,
Google Research
Graph Mining and Data Efficiency@Scale—From scalability to ML applications
Tue Dec 5, 2023
Nishil Talati,
University of Michigan
High-Performance GPU Code Generation for Mining Motifs in Temporal Graphs
Tue Oct 17, 2023
Rohan Yadav,
Stanford University
Distributed Sparse Computing in Python
Thu May 11, 2023
Gal Sela,
Technion - Israel Institute of Technology
Size Operation for Concurrent Data Structures
Thu Apr 20, 2023
Jialin Li,
National University of Singapore
The Case for Network Ordering in Distributed Systems Design
Wed Oct 5, 2022
Rezaul Chowdhury,
Stony Brook University
Fast Stencil Computations using FFT and Gaussian Approximations
Wed Sep 28, 2022
Harsha Simhadri,
Microsoft Research
Approximate Nearest Neighbor Search algorithms for web-scale search and recommendation
Wed Sep 14, 2022
David Tench,
Rutgers University
Dynamic Graph Connectivity—To Infinity And Beyond
Wed Jun 1, 2022
Hans Vandierendonck,
Queen's University Belfast
Memory Locality Optimisations for Graph Processing
Wed Apr 20, 2022
Jessica Shi,
MIT
Bridging Theory and Practice in Parallel Subgraph Computations
Wed Apr 6, 2022
Neil Thompson,
MIT
How close are algorithms to being optimal?
Wed Feb 16, 2022
William Kuszmaul,
MIT
Linear Probing Revisited—Tombstones Mark the Demise of Primary Clustering
Wed Dec 8, 2021
Yuanhao Wei,
CMU
Multi-point Queries on Concurrent Data Structures
Wed Nov 17, 2021
Naama Ben-David,
VMware Research
Algorithms for Practical Distributed Agreement
Wed Nov 3, 2021
Irene Zhang,
Microsoft Research
The Demikernel Datapath OS Architecture for Microsecond-scale Datacenter Systems
Wed Oct 13, 2021
Jan Vitek,
Northeastern University
Productivity and Performance Reconciled—The Julia Story
Wed May 12, 2021
Daniel Lemire,
University of Quebec
Parsing numbers at a gigabyte per second
Wed Apr 28, 2021
Xuhao Chen,
MIT
Software and Hardware Systems for Emerging Graph Algorithms
Wed Apr 7, 2021
Helen Xu,
MIT
Data Structure Design for Skewed Dynamic Graph Processing
Wed Mar 31, 2021
Tim Davis,
Texas A&M
SuiteSparse:GraphBLAS—graph algorithms in the language of sparse linear algebra
Wed Mar 24, 2021
Martin Farach-Colton,
Rutgers University
The Algorithmics of Address Translation
Wed Mar 17, 2021
Maryam Mehri Dehnavi,
University of Toronto
Inspecting Irregular Computation Patterns to Generate Fast Code
Wed Mar 10, 2021
Sam Westrick,
CMU
Disentanglement—Provably Efficient Parallel Functional Programming (Slides)
Wed Feb 24, 2021
Edgar Solomonik,
UIUC
Scalable Algorithms for Tensor Computations (Slides)
Mon Jan 25, 2021
Ariful Azad,
Indiana University
Computational Building Blocks for Machine Learning on Graphs (Slides)
Mon Jan 11, 2021
Xuehai Qian,
USC
High Performance Graph Mining Systems (Slides)
Mon Dec 7, 2020
Yuanming Hu,
MIT
Taichi—A Language for High-Performance Computation on Spatially Sparse Data Structures
Mon Nov 30, 2020
Scott Beamer,
UC Santa Cruz
Efficiently Exploiting Low-Activity Factors to Accelerate RTL Simulation
Mon Nov 9, 2020
Bradley Kuszmaul,
Google
Everyone Loves File—File Storage Service (FSS) in Oracle Cloud Infrastructure
Mon Nov 2, 2020
Michael Bender,
Stony Brook University
Filters
Mon Oct 26, 2020
Alex Pothen,
Purdue University
Approximation—A Paradigm for Designing Parallel Graph Algorithms
Mon Oct 19, 2020
Rezaul Chowdhury,
Stony Brook University
Automatic Derivation of Efficient Parallel Recursive Divide-&-Conquer Algorithms for Dynamic Programs
Mon Sep 28, 2020
Michael Mahoney,
ICSI and UC Berkeley
ADAHESSIAN—An Adaptive Second Order Optimizer for Machine Learning
Mon Sep 21, 2020
Franz Franchetti,
Carnegie Mellon University
SPIRAL's Operator Language—From Textbook Math to High Performance—With Correctness Guarantees
Mon Aug 10, 2020
James Demmel,
UC Berkeley
Communication-avoiding algorithms for linear algebra, machine learning and beyond
Mon Aug 3, 2020
Kathy Yelick,
UC Berkeley/ Lawrence Berkeley National Lab
Genomic Analysis and Learning at Scale—Mapping Irregular Computations to Advanced Architectures
Mon Jul 27, 2020
Larry Rudolph and Steven Martin,
Two Sigma Investments, LP/ MIT CSAIL
QuickQuery—GPU-Based Approximate Query Processing for Sub-Second Exploration at Scale
Mon Jul 20, 2020
Stephen Chou,
MIT
Format Abstractions for Sparse Tensor Algebra Compilation
Mon Jul 13, 2020
Michael Axtmann and Peter Sanders,
Karlsruhe Institute of Technology
Engineering Scalable Parallel Sorting Algorithms
Mon Jun 29, 2020
Umit Catalyurek,
Georgia Tech
Fast graph analytics on heterogenous and deep-memory architectures
Mon Jun 22, 2020
Aydin Buluc,
Lawrence Berkeley National Lab/UC Berkeley
Sparse Matrices Beyond Solvers—Graphs, Biology, and Machine Learning (Slides)
Mon Jun 15, 2020
Wen-Mei Hwu,
UIUC
Fast GPU Code for Graphs (Slides)
Mon Jun 8, 2020
David Bader,
New Jersey Institute of Technology
Solving Global Grand Challenges with High Performance Data Analytics
Mon Jun 1, 2020
John Owens,
UC Davis
Dynamic Data Structures on the GPU
Mon May 11, 2020
Alex Aiken,
Stanford
Program Optimization for Machine Learning
Mon May 4, 2020
Ariya Shajii,
MIT
Seq—a high-performance language for bioinformatics
Mon Apr 20, 2020
Neil Thompson & Yash Sherry,
MIT
How fast are Algorithms Improving?
Tue Feb 18, 2020
S. Tucker Taft,
AdaCore
Safe Parallel Programming -- ParaSail, Ada 202X, OpenMP, and Rust
Mon Nov 25, 2019
Bruce Maggs,
Duke University and Emerald Innovations
A Speed-of-Light Internet Service Provider
Mon Nov 18, 2019
Charith Mendis,
MIT
How to Modernize Compiler Technology
Mon Nov 4, 2019
Yunming Zhang,
MIT
GraphIt—A Domain-Specific Language for Writing High-Performance Graph Applications
Mon Oct 21, 2019
Alex Conway,
Rutgers University
SplinterDB—Closing the Bandwidth Gap on NVMe
Mon Sep 30, 2019
Valentin Churavy,
MIT
Julia—Making dynamic programs run fast
Mon Sep 23, 2019
Riyadh Baghdadi,
MIT
Tiramisu—A Polyhedral Compiler for Dense and Sparse Deep Learning
Mon Sep 16, 2019
Bill Dally,
NVIDIA Corporation and Stanford University
Domain-Specific Accelerators
Tue Aug 27, 2019
Laxman Dhulipala,
Carnegie Mellon University
Algorithms and Systems for Processing Massive Static and Evolving Graphs
Tue Aug 20, 2019
Tao B. Schardl,
MIT
Tapir—Embedding Recursive Fork-Join Parallelism into LLVM's Intermediate Representation
Tue Aug 6, 2019
Jeremy Kepner,
MIT Lincoln Laboratory Supercomputing Center
Optimal system settings—How to not lose before you begin
Tue Jul 30, 2019
I-Ting Angelina Lee,
Washington University in St. Louis
Advances in Determinacy Race Detection for Task-Parallel Code
Tue Jul 23, 2019
Maurice Herlihy,
Brown University
Speculative Concurrency for Ethereum Smart Contracts
Tue Jul 16, 2019
Song Han,
MIT
AutoML for Efficiently Designing Efficient Neural Network Architectures
Tue Jul 9, 2019
Fredrik Kjolstad,
MIT
The Sparse Tensor Algebra Compiler
Tue Jun 11, 2019
Charles Leiserson,
MIT
The Resurgence of Software Performance Engineering