AbstractResearchGroup
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ABSTRACT @ CMU
The ABSTRACT research group at CMU is the research group of Brandon Lucia. Our group does research at the intersection of computer architecture, computer systems, and programming languages. Our research focuses on improving the programmability, reliability, and efficiency of computing devices and systems. Our work cuts across the layers of the system stack, from the microarchitecture to the application, often touching on everything in between.
Research
Our group does research into computer systems. We currently have a focus on (1) Intermittent and Energy-harvesting computing, (2) Concurrency, Parallelism, Consistency, and Approximation.
Intermittent and Energy-harvesting Computing Devices
We are working to define the system stack for intermittent computing devices, like ones that harvest energy from their environment. Our goal is to make these devices programmable, reliable, low-power, and robust to common-case power failures. Making these devices useful requires us to rethink the whole system stack to deal with complexity and reliability, from programming abstractions tolerant of interruptions, down to super-energy-efficient circuits we use to implement microarchitectural features tolerant of byzantine failures.
An Energy-interference-free Hardware/Software Debugger for Intermittent Energy-harvesting Systems Alexei Colin, Graham Harvey, Brandon Lucia, Alanson Sample ASPLOS 2016
Energy-interference-free System and Toolchain Support for Energy-harvesting Devices Alexei Colin, Alanson Sample, Brandon Lucia CASES 2015 (short paper)
A Simpler, Safer Programming and Execution Model for Intermittent Systems Brandon Lucia, Benjamin Ransford PLDI 2015
Concurrency and Parallelism
We are developing software tools & techniques and hardware & architectural features to make concurrent and parallel computer systems correct, reliable, and efficient. We research new parallel computer architectures that make systems safer and make programming easier, hardware-software solutions that automate debugging, and architectures, compilers, and runtimes that avoid failures in broken programs. An especially exciting topic in this area is approximate computing, which trades off correctness for increased performance and programmability. We are investigating all of these topics in emerging large-scale homogeneous and heterogeneous systems. Our work leverages algorithmic and execution-level approximation, statistical inference, symbolic execution, and dynamic analysis in novel ways to make systems behave better.
Production-guided Concurrency Debugging Nuno Machado (IST), Brandon Lucia, Luis Rodrigues (IST) PPoPP 2016
Valor: Efficient, Software-Only Region Conflict Exceptions Swarnendu Biswas (OSU), Minjia Zhang (OSU), Michael D. Bond (OSU), Brandon Lucia OOPSLA 2015, OOPSLA'15 Distinguished Paper Award, OOPSLA'15 Distinguished Artifact Award
Concurrency Debugging with Differential Schedule Projections Nuno Machado (IST), Luis Rodrigues (IST), Brandon Lucia PLDI 2015
Systems Should Automatically Specialize Code and Data Brandon Lucia and Todd Mytkowicz (MSR) Approx 2014
People
Lab Squad (L to R): Vignesh, Dhruva, Brandon, Alanson (DRP), Alexei, Preeti
Faculty
PhD Students
Nuno Machado (summer 2015 Visiting Scholar, from IST Lisboa)
Vignesh Balaji
Masters Students
Dhruva Tirumala
Preeti Upendra Murthy
Undergraduates
Naveen Setlur (Sophomore @ CMU ECE)
Junhong Li (Sophomore @ CMU ECE)
Alumni
Mark McElwaine (now a junior at CMU)
Graham Harvey (now an Imagineer @ Disney)
High School Interns
Savi Medlang (Now a freshman at Wake Forest College)
External Collaborators
Alanson Sample (Disney Research Pittsburgh)
Joe Devietti (University of Pennsylvania)
Mike Bond (The Ohio State University)
Support
Our work is generously supported by a gift from Disney Research Pittsburgh, a 2015 Google Faculty Research Award, the 2015 Bell Labs Prize, and the National Science Foundation (grant CNS-1526342).
