[LLVM] Add intrinsics for RISC-V Bitmap extension

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Zbb extension: https://reviews.llvm.org/D99320 https://reviews.llvm.org/D99319 Zbc extension: https://reviews.llvm.org/D99711 https://reviews.llvm.org/D99712 Zbe extension: https://reviews.llvm.org/D101143 https://reviews.llvm.org/D101144 Zbf extension: Zbm extension: https://reviews.llvm.org/D101248 https://reviews.llvm.org/D101249 Zbp extension: https://reviews.llvm.org/D100830 https://reviews.llvm.org/D100831 Zbr extension: https://reviews.llvm.org/D99009 https://reviews.llvm.org/D99008 Zbt extension: Let’s take a look for those patches and what needs to done for those intrinsic on llvm, In: We defined two new classes that’s derived form base… Read more [LLVM] Add intrinsics for RISC-V Bitmap extension

[GCC] RISC-V: Add patterns for builtin overflow.

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This patch has been committed to the master branch: https://gcc.gnu.org/pipermail/gcc-patches/2021-April/569135.html https://gcc.gnu.org/git/?p=gcc.git;a=commit;h=6efd040c301b06fae51657c8370ad940c5c3d513 Learn more about Built-in Functions about Performing Arithmetic with Overflow Checking: https://gcc.gnu.org/onlinedocs/gcc/Integer-Overflow-Builtins.html Since these functions are pervasively used in the kernel, driver, etc. Adding patterns to the RISC-V backend should allow us to have some performance elevation. Some example: https://android.googlesource.com/kernel/common.git/+/refs/tags/ASB-2019-03-05_4.9/include/linux/overflow.h https://lwn.net/Articles/623368/ Let’s start with… Read more [GCC] RISC-V: Add patterns for builtin overflow.

[GCC] RISC-V: Avoid zero/sign extend for volatile loads.

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This bug was initially raised by one of the developers on GCC Bugzilla https://gcc.gnu.org/bugzilla/show_bug.cgi?id=97417 Where for a simple volatile load/store like: gcc will generate: However, the definition of lbu from RISC-V spec mentioned: ” The LW instruction loads a 32-bit value from memory and sign-extends this to 64 bits before storing it in register rd… Read more [GCC] RISC-V: Avoid zero/sign extend for volatile loads.

Momus — An image processing tool

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Momus is a cross-platform image processing tool that designed to counter AI censorship on social media platforms. Momus是一款用来绕过社交平台AI图片匹配的跨平台工具 Github: https://github.com/LevyHsu/Momus Download exe release: https://github.com/LevyHsu/Momus/releases Online Demo: http://direct.momus.levyhsu.com/ Monus uses SIFT（Scale Invariant Feature Transform） from OpenCV to detect all keypoint on the image then inject noise to avoid auto-detection. Monus使用opencv库中的SIFT（Scale Invariant Feature Transform）算法来标记所有的关键点，然后添加噪音来避免社交平台的图片自动匹配。 Library: Install: run:… Read more Momus — An image processing tool

ZDNS-Flask

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A simple implementation for using Zdns on a Web browser ( ZDNS is a command-line utility that provides high-speed DNS lookups. ) Github: https://github.com/LevyHsu/ZDNS-Flask Although authentication is implemented, it’s still recommended that you use this app on a local network instead of a public network. Also, use it at your own risk! Install Dependencies: sudo… Read more ZDNS-Flask

SON algorithm for Frequent Itemsets

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Python3 implementation of : Randomized Algorithm (Chapter 6.4.1) Savasere, Omiecinski, and Navathe (SON) Algorithm (Chapter 6.4.3) Originally described in Book Mining of Massive Datasets. Book is available online: http://infolab.stanford.edu/~ullman/mmds/ch6.pdf Datasets Used ( T10I4D100K, T40I10D100K ): http://fimi.ua.ac.be/data/ Arguments: -f –file Filename -s –min_support (default 0.5) Minimal support rate. -c –min_confidence (default 0.5) Minimal confidence level. -t… Read more SON algorithm for Frequent Itemsets

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CF-Cannon V2

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Github Link CF-Cannon V2 is a tool written in python to perform layer 7 stress tests on your own server. V2 version enables distributed attack on each node with penetration of the UAM page and can be (theoretically) deployed on infinite machines. Disclaimer: Please make sure all your tests are legal and with the consent… Read more CF-Cannon V2

Page Rank Algorithm

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Following codes are used for Big Data Assignment 2: Given the Google web graph: http://snap.stanford.edu/data/web-Google.html File Format: Three modes are written in this script: Graph Mode: Use NetworkX and Graph to connect all nodes and edges. (Fastest and recommended, also default mode) Matrix Mode: Textbook method, convert all nodes and edges to the Stochastic matrix,… Read more Page Rank Algorithm