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acstor

In virtualized data centers, the access of virtual disk images (VDIs) is critical for the overall system performance. As the system scales up to a large number of running VMs, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. We propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue, which can dynamically balance the traffic workloads in accessing VDI chunks based on the run-time network state.

advclip

The implementation of our ACM MM 2023 paper "AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning"

advencoder

The implementation of our ICCV 2023 paper "Downstream-agnostic Adversarial Examples"

advhash

The official implementation of our ACM MM 2021 paper "AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch".

afl-fi

amain

Detecting Semantic Code Clones by Building AST-based Markov Chains Model

amt-gan

The official implementation of our CVPR 2022 paper "Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer".

android-container

Method on running Linux containers (Docker) on the android platform. Migrate container from X86-Based ubuntu to ARM-Based android.

androidx

AndroidX is a customizable execution runtime environment for running Android applications on clouds

ann-es

arb-detector

This repo based on Pul and graph learning which can help detect arbitrary addresses

ares

Ares is a high performance and fault tolerant distributed stream processing system, which considers both both system performance and fault tolerant capability during task allocation and use a game-theoretic approach to obtain an optimal scheduler for task allocation. Ares greatly outperforms Storm in terms of system throughput and the average processing latency.

argus

Argus is a novel RDMA-assisted job scheduler which achieves high resource utilization by fully exploiting the structure feature of stage dependency. Comprehensive experiments using large-scale traces collected from real world show that Argus reduces job completion time and job makespan by 21% and 20%, respectively, compared to RDMA-Spark.

attack_ptmc

The dataset, source code and the results of our ESEC/FSE 2023 paper "An Extensive Study on Adversarial Attack against Pre-trained Models of Code".

auxo

Auxo is a scalable and efficient framework for graph stream summarization

awesome-code-intelligence

badhash

The official implementation of BadHash

bcf

Better Choice Cuckoo Filter (BCF) is an efficient approximate set representation data structure. Different from the standard Cuckoo Filter (CF), BCF leverages the principle of the power of two choices to select the better candidate bucket during insertion. BCF reduces the average number of relocations of the state-of-the-art CF by 35%.

bcts.github.io

Homepage for bcts research group

bkrcd

Fast algorithm for enumerating maximal cliques in real-world graphs.

blocksim

A blockchain network simulator, which can be used for blockchain network protocol verification.

cag

causalnet

chartstamp

The implementation of ACM MM 2022 paper "ChartStamp: Robust Chart Encoding for Real-World Applications".

climber

code_summarization_meta

covid19-dataset

The labeled news data about coronavirus pneumonia.

cross-links-bias

Implementation for NeurIPS 2023 paper: Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective

dcf

Dynamic Cuckoo Filter (DCF) is succinct data structure of approximate set representing and membership testing for large-scale dynamic data sets. DCF supports item insertion/deletion/query, and can flexibly adjust its capacity. A DCF reduces the memory space of the state-of-the-art Dynamic Bloom Filter significantly by 75% as well as greatly improving the speeds of insert/query/delete operation by 30% to 80%.

dgraph

DGraph is a system for directed graph processing with taking advantage of the strongly connected component structure. On this system, most graph partitions are able to reach convergence in order and need to be loaded into the main memory for exactly once, getting much lower data access cost and faster convergence.