Parallel Architecture, System, and Algorithm (PASA) Lab at the Electrical Engineering and Computer Science, University of California, Merced performs research in core technologies for large-scale parallel systems. The core theme of our research is to study how to enable scalable and efficient execution of enterprise and scientific applications on increasingly complex large-scale parallel systems. Our work creates innovation in runtime, architecture, performance modeling, and programming models; We also investigate the impact of novel architectures (e.g., non-volatile memory and accelerator with massive parallelism) on the designs of applications and runtime. Our goal is to improve the performance, reliability, energy efficiency, and productivity of large-scale parallel systems.
[9/2020] A paper “HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory” is accepted in NeurIPS'20!
[9/2020] Congratulate Jiawen for his internship in the Facebook research!
[8/2020] The lab has a new website! :)
[8/2020] A paper “MATCH: An MPI Fault Tolerance Benchmark Suite” is accepted in IISWC'20.
[7/2020] A paper “Exploring Non-Volatility of Non-Volatile Memory for High Performance Computing Under Failures” is accepted in Cluster’20.
[6/2020] A paper “Ribbon: High Performance Cache Line Flushing for Persistent Memory” is accepted in PACT’20.
[6/2020] A paper “Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation” is accepted in SC’20.
[3/2020] Congratulations to Jie Ren, Kai, Jie Liu, Jiawen and Wenqian for their summer internships in Microsoft research, ByteDance, Futurewei and PNNL!
[3/2020] A paper “RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices” is accepted in USENIX OpML’20.
[2/2020] A paper “Flame: A Self-Adaptive Auto-Labeling System for Heterogeneous Mobile Processors” is accepted in On-Device Intelligence Workshop at MLSys’20.
[1/2020] Dong was invited to join IEEE Transactions on Parallel and Distributed Systems (TPDS) Review Board.