Peng Jiang, Ph.D.
Assistant Professor
Emeriti-Faculty Scholar
Biography
Research Interests
- Compiler and runtime support for high-performance machine learning
- Parallelization for data-intensive and compute-intensive applications
- Programming models for irregular applications
Research Interests (Keywords)
High-Performance Computing
Selected Publication
- Peng Jiang, Linchuan Chen, Gagan Agrawal. Revealing Parallel Scans and Reductions in Recurrences through Function Reconstruction. The 27th International Conference on Parallel Architectures and Compilation Techniques
- Peng Jiang, Gagan Agrawal. A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication. Thirty-second Conference on Neural Information Processing Systems
- Peng Jiang, Gagan Agrawal. Combining SIMD and Many/Multi-core Parallelism for Finite State Machines with Enumerative Speculation. Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
- Peng Jiang, Gagan Agrawal. Efficient SIMD and MIMD Parallelization of Hash-based Aggregation by Conflict Mitigation. Proceedings of the 2017 International Conference on Supercomputing
Research areas
- Verifiable, Dependable, and High-Performance Systems