Hi! I am currently a Research Scientist at the Architecture Research Group (ARG) at NVIDIA

Before joining NVIDIA, I was a PhD candidate at the ECE department at Carnegie Mellon University where I worked with Professor Brandon Lucia

NOTE: Please do not send an email at my CMU ID (I will not have access to that account for much longer)

Research Interests

My dissertation research focused on developing architectural support for optimizing irregular applications (particularly, graph processing applications).

Graph processing is an important domain that is hard to optimize because of the irregular memory access pattern and the scale of input graphs. My research aims to accelerate graph processing on multi-core processors by improving cache locality and scalability of parallel graph processing workloads. A fundamental tenet of the research is to exploit the structural properties of input graphs to propose input-specific locality optimizations.

In the past, I also worked on extending cache coherence protocols and exploiting approximate computing to improve scalability of parallel applications.

Publications

"P-OPT: Practical Optimal Cache Replacement for Graph Analytics",
Vignesh Balaji, Neal Crago, Aamer Jaleel, and Brandon Lucia,
International Symposium on High Performance Computer Architecture (HPCA 2021)
(BEST PAPER NOMINEE)
[paper] [slides] [teaser] [talk] [github]

"Optimizing Graph Processing and Preprocessing with Hardware Assisted Propagation Blocking",
Vignesh Balaji, and Brandon Lucia,
ArXiv 2020
[paper]

"Peacenik: Architecture Support for Not Failing under Fail-Stop Memory Consistency",
Rui Zhang, Swarnendu Biswas, Vignesh Balaji, Michael D. Bond, and Brandon Lucia,
International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2020)
[paper] [slides] [github]

"Combining Data Duplication and Graph Reordering to Accelerate Parallel Graph Processing",
Vignesh Balaji, and Brandon Lucia,
International Symposium on High-Performance Parallel and Distributed Computing (HDPC 2019)
[paper] [slides] [github]

"When is Graph Reordering an Optimization? Studying the effect of lightweight graph reordering across applications and input graphs",
Vignesh Balaji, and Brandon Lucia,
IEEE International Symposium on Workload Characterization (IISWC 2018)
(BEST PAPER AWARD)
[preprint] [slides] [github]

"Flexible Support for Fast Parallel Commutative Updates",
Vignesh Balaji, Dhruva Tirumala and Brandon Lucia,
ArXiv 2018
[paper]

"An Architecture and Programming Model for Accelerating Parallel Commutative Computations via Privatization",
Vignesh Balaji, Dhruva Tirumala and Brandon Lucia,
Symposium on Principles and Practice of Parallel Programming (PPoPP 2017)
[poster]

"Intermittent Computing: Challenges and Opportunities",
Brandon Lucia, Vignesh Balaji, Alexei Colin, Kiwan Maeng, and Emily Ruppel,
Summit on Advances in Programming Languages (SNAPL 2017)
[paper]

"Overcoming the Data-flow Limit on Parallelism with Structural Approximation",
Vignesh Balaji, Brandon Lucia, and Radu Marculescu,
Workshop on Approximate Computing (WAX) colocated with (ASPLOS 2016)
[paper]

Interesting Stuff

A small collection of enlightening articles/papers/opinions...
[StrongInference]
[You-and-your-research]
[Technology-and-courage]

Contact