期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
Growing accuracy and robustness of Deep Neural Networks (DNN) models are accompanied by growing model capacity (going deeper or wider). However, high ......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
Sparse triangular solve (SpTRSV) is one of the most important kernels in many real-world applications. Currently, much research on parallel SpTRSV foc......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
Replicas of a vertex play an important role in existing distributed graph processing systems which make a single vertex to be parallel processed by mu......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
Performance variance becomes increasingly challenging on current large-scale HPC systems. Even using a fixed number of computing nodes, the execution ......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
General sparse matrix-matrix multiplication (SpGEMM) is an essential building block in a number of applications. In our work, we fully utilize GPU reg......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
In this paper, we propose an in-memory computing framework (called GPF) that provides a set of genomic formats, APIs and a fast genomic engine for lar......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
In large-scale data-parallel analytics, shuffle, or the cross-network read and aggregation of partitioned data between tasks with data dependencies, u......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (1)
Going deeper and wider in neural architectures improves their accuracy, while the limited GPU DRAM places an undesired restriction on the network desi......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
Nonvolatile processors have emerged as one of the promising solutions for energy harvesting scenarios, among which Wireless Sensor Networks (WSN) prov......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
Many important graph applications are iterative algorithms that repeatedly process the input graph until convergence. For such algorithms, graph abstr......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
In-Memory cluster Computing (IMC) frameworks (e.g., Spark) have become increasingly important because they typically achieve more than 10x speedups ov......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
It is crucial for distributed systems to achieve high availability. Unfortunately, this is challenging given the common component failures (i.e., faul......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
Recently, mobile applications have gradually become performance and resource intensive, which result in a massive battery power drain and high surface......
期刊： ACM SIGPLAN NOTICES, 2018; 53 (2)
Fast, byte-addressable non-volatilememory (NVM) embraces both near-DRAM latency and disk-like persistence, which has generated considerable interests ......
