In this paper, we present AFL++, a community-driven open-source tool that incorporates
state-of-the-art fuzzing research, to make the research comparable, reproducible …

Modern neural networks are increasingly bottlenecked by the limited capacity of on-device
GPU memory. Prior work explores dropping activations as a strategy to scale to larger neural …

Deep-learning (DL) compilers such as TVM and TensorRT are increasingly being used to
optimize deep neural network (DNN) models to meet performance, resource utilization and …

Many program analyses benefit, both in precision and performance, from precise pointer
analysis. An important dimension of pointer analysis precision is flow-sensitivity, which has …

Abstract Software Fault Isolation (SFI) is an effective approach to sandboxing binary code of
questionable provenance, an interesting use case for native plugins in a Web browser. We …

In this paper we advocate that it is time for a radical rethinking of database systems design.
Developers should be able to leverage high-level programming languages without having to …

Various applications model problems as streaming graphs, which need to quickly apply a
stream of updates and run algorithms on the updated graph. Furthermore, many dynamic …

In the past decade, Deep Learning (DL) systems have been widely deployed in various
application domains to facilitate our daily life, eg, natural language processing, healthcare …

Non-volatile memory (NVM) provides a scalable and power-efficient solution to replace
DRAM as main memory. However, because of relatively high latency and low bandwidth of …

Pointer analysis is a prerequisite for many program analyses, and the effectiveness of these
analyses depends on the precision of the pointer information they receive. Two major axes …