w32zhong

linenoise

A small self-contained alternative to readline and libedit

search-engine

A math-aware search engine.

parson

Lightweight JSON library written in C.

tkarch

Arch OS install and setup scripts

BTreeimplementation

CSC 541 Assignment 4 B-Trees Introduction The goals of this assignment are two-fold: To introduce you to searching data on disk using B-trees. To investigate how changing the order of a B-tree affects its performance. Index File During this assignment you will create, search, and manage a binary index file of integer key values. The values stored in the file will be specified by the user. You will structure the file as a B-tree. Program Execution Your program will be named assn_4 and it will run from the command line. Two command line arguments will be specified: the name of the index file, and a B-tree order. assn_4 index-file order For example, executing your program as follows assn_4 index.bin 4 would open an index file called index.bin that holds integer keys stored in an order-4 B-tree. You can assume order will always be ≥ 3. For convenience, we refer to the index file as index.bin throughout the remainder of the assignment. Note. If you are asked open an existing index file, you can assume the B-tree order specified on the command line matches the order that was used when the index file was first created. B-Tree Nodes Your program is allowed to hold individual B-tree nodes in memory—but not the entire tree—at any given time. Your B-tree node should have a structure and usage similar to the following. #include <stdlib.h> int order = 4; /* B-tree order */ typedef struct { /* B-tree node */ int n; /* Number of keys in node */ int *key; /* Node's keys */ long *child; /* Node's child subtree offsets */ } btree_node; btree_node node; /* Single B-tree node */ node.n = 0; node.key = (int *) calloc( order - 1, sizeof( int ) ); node.child = (long *) calloc( order, sizeof( long ) ); Note. Be careful when you're reading and writing data structures with dynamically allocated memory. For example, trying to write node like this fwrite( &node, sizeof( btree_node ), 1, fp ); will write node's key count, the pointer value for its key array, and the pointer value for its child offset array, but it will not write the contents of the key and child offset arrays. The arrays' contents and not pointers to their contents need to be written explicitly instead. fwrite( &node.n, sizeof( int ), 1, fp ); fwrite( node.key, sizeof( int ), order - 1, fp ); fwrite( node.child, sizeof( long ), order, fp ); Reading node structures from disk would use a similar strategy. Root Node Offset In order to manage any tree, you need to locate its root node. Initially the root node will be stored near the front of index.bin. If the root node splits, however, a new root will be appended to the end of index.bin. The root node's offset will be maintained persistently by storing it at the front of index.bin when the file is closed, and reading it when the file is opened. #include <stdio.h> FILE *fp; /* Input file stream */ long root; /* Offset of B-tree root node */ fp = fopen( "index.bin", "r+b" ); /* If file doesn't exist, set root offset to unknown and create * file, otherwise read the root offset at the front of the file */ if ( fp == NULL ) { root = -1; fp = fopen( "index.bin", "w+b" ); fwrite( &root, sizeof( long ), 1, fp ); } else { fread( &root, sizeof( long ), 1, fp ); } User Interface The user will communicate with your program through a set of commands typed at the keyboard. Your program must support four simple commands: add k Add a new integer key with value k to index.bin. find k Find an entry with a key value of k in index.bin, if it exists. print Print the contents and the structure of the B-tree on-screen. end Update the root node's offset at the front of the index.bin, and close the index file, and end the program. Add Use a standard B-tree algorithm to add a new key k to the index file. Search the B-tree for the leaf node L responsible for k. If k is stored in L's key list, print Entry with key=k already exists on-screen and stop, since duplicate keys are not allowed. Create a new key list K that contains L's keys, plus k, sorted in ascending order. If L's key list is not full, replace it with K, update L's child offsets, write L back to disk, and stop. Otherwise, split K about its median key value km into left and right key lists KL = (k0, ... , km-1) and KR = (km+1, ... , kn-1). Use ceiling to calculate m = ⌈(n-1)/2⌉. For example, if n = 3, m = 1. If n = 4, m = 2. Save KL and its associated child offsets in L, then write L back to disk. Save KR and its associated child offsets in a new node R, then append R to the end of the index file. Promote km , L's offset, and R's offset and insert them in L's parent node. If the parent's key list is full, recursively split its list and promote the median to its parent. If a promotion is made to a root node with a full key list, split and create a new root node holding km and offsets to L and R. Find To find key value k in the index file, search the root node for k. If k is found, the search succeeds. Otherwise, determine the child subtree S that is responsible for k, then recursively search S. If k is found during the recursive search, print Entry with key=k exists on-screen. If at any point in the recursion S does not exist, print Entry with key=k does not exist on-screen. Print This command prints the contents of the B-tree on-screen, level by level. Begin by considering a single B-tree node. To print the contents of the node on-screen, print its key values separated by commas. int i; /* Loop counter */ btree_node node; /* Node to print */ long off; /* Node's offset */ for( i = 0; i < node.n - 1; i++ ) { printf( "%d,", node.key[ i ] ); } printf( "%d", node.key[ node.n - 1 ] ); To print the entire tree, start by printing the root node. Next, print the root node's children on a new line, separating each child node's output by a space character. Then, print their children on a new line, and so on until all the nodes in the tree are printed. This approach prints the nodes on each level of the B-tree left-to-right on a common line. For example, inserting the integers 1 through 13 inclusive into an order-4 B-tree would produce the following output. 1: 9 2: 3,6 12 3: 1,2 4,5 7,8 10,11 13 To support trees with more than 9 levels, we leave space for two characters to print the level at the beginning of each line, that is, using printf( "%2d: ", lvl )" or something similar. Hint. To process nodes left-to-right level-by-level, do not use recursion. Instead, create a queue containing the root node's offset. Remove the offset at the front of the queue (initially the root's offset) and read the corresponding node from disk. Append the node's non-empty subtree offsets to the end of the queue, then print the node's key values. Continue until the queue is empty. End This command ends the program by writing the root node's offset to the front of index.bin, then closing the index file. Programming Environment All programs must be written in C, and compiled to run on the remote.eos.ncsu.edu Linux server. Any ssh client can be used to access your Unity account and AFS storage space on this machine. Your assignment will be run automatically, and the output it produces will be compared to known, correct output using diff. Because of this, your output must conform to the print command's description. If it doesn't, diff will report your output as incorrect, and it will be marked accordingly. Supplemental Material In order to help you test your program, we provide example input and output files. input-01.txt, an input file of commands applied to an initially empty index file saved as an order-4 B-tree, and input-02.txt, an input file of commands applied to the index file produced by input-01.txt. The output files show what your program should print after each input file is processed. output-01.txt, the output your program should produce after it processes input-01.txt. output-02.txt, the output your program should produce after it processes input-02.txt. To test your program, you would issue the following commands: % rm index.bin % assn_4 index.bin 4 < input-01.txt > my-output-01.txt % assn_4 index.bin 4 < input-02.txt > my-output-02.txt You can use diff to compare output from your program to our output files. If your program is running properly and your output is formatted correctly, your program should produce output identical to what is in these files. Please remember, the files we're providing here are meant to serve as examples only. Apart from holding valid commands, you cannot make any assumptions about the size or the content of the input files we will use to test your program. Test Files The following files were used to test your program. Order 3 Test Case. input-03.txt output-03-first.txt Order 4 Test Case. input-04.txt output-04-first.txt Order 10 Test Case. input-10-01.txt, input-10-02.txt output-10-01.txt, output-10-02.txt Order 20 Test Case. input-20.txt output-20-first.txt Your program was run on all test cases using order-3, order-4, and order-20 B-trees. % rm index.bin % assn_4 index.bin 3 < input-03.txt > my-output-03.txt % rm index.bin % assn_4 index.bin 4 < input-04.txt > my-output-04.txt % rm index.bin % assn_4 index.bin 20 < input-20.txt > my-output-20.txt Your program was also run twice using an order-10 B-tree, to test its ability to re-use an existing index file. % rm index.bin % assn_4 index.bin 10 < input-10-01.txt > my-output-10-01.txt % assn_4 index.bin 10 < input-10-02.txt > my-output-10-02.txt Hand-In Requirements Use Moodle (the online assignment submission software) to submit the following files: assn_4, a Linux executable of your finished assignment, and all associated source code files (these can be called anything you want). There are four important requirements that your assignment must satisfy. Your executable file must be named exactly as shown above. The program will be run and marked electronically using a script file, so using a different name means the executable will not be found, and subsequently will not be marked. Your program must be compiled to run on remote.eos.ncsu.edu. If we cannot run your program, we will not be able to mark it, and we will be forced to assign you a grade of 0. Your program must produce output that exactly matches the format described in the print command section of this assignment. If it doesn't, it will not pass our automatic comparison to known, correct output. You must submit your source code with your executable prior to the submission deadline. If you do not submit your source code, we cannot MOSS it to check for code similarity. Because of this, any assignment that does not include source code will be assigned a grade of 0. Updated 20-Dec-14

mnn

Manual Neural Networks (MNN) using CuPy (for learning purpose)

OPMES

Research reference version of an old OPMES prototype.

sql-sample-data

Database System Concepts 6th edition: University Sample Schema Data

study-lucene

Study Lucene from old source code.

tknet

a cross-platform P2P library

w32zhong/llm.c

LLM training in simple, raw C/CUDA

w32zhong/w32zhong.github.io

w32zhong/BitDelta

w32zhong/blackmamba-fork

w32zhong/causal-conv1d

Causal depthwise conv1d in CUDA, with a PyTorch interface

w32zhong/cllm_fork

w32zhong/CS-Drafting

Cascade Speculative Drafting

w32zhong/DeepSeek-Math

w32zhong/EAGLE

EAGLE: Lossless Acceleration of LLM Decoding by Feature Extrapolation

w32zhong/filebrowser

📂 Web File Browser

w32zhong/laser

The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction

w32zhong/mamba

w32zhong/marker

Convert PDF to markdown quickly with high accuracy

w32zhong/MCSD

Multi-Candidate Speculative Decoding

w32zhong/Medusa

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

w32zhong/minbpe

Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.

w32zhong/Ouroboros

Ouroboros: Speculative Decoding with Large Model Enhanced Drafting

w32zhong/Progressive-Hint

This is the official implementation of "Progressive-Hint Prompting Improves Reasoning in Large Language Models"

w32zhong/pytorch-that-I-successfully-built

Tensors and Dynamic neural networks in Python with strong GPU acceleration

w32zhong/rerope

Rectified Rotary Position Embeddings

w32zhong/search_with_lepton

Building a quick conversation-based search demo with Lepton AI.

w32zhong/SeeAct

SeeAct is a system for generalist web agents that autonomously carry out tasks on any given website, with a focus on large multimodal models (LMMs) such as GPT-4V(ision).

w32zhong/self-speculative-decoding

Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**

w32zhong/Sequoia

scalable and robust tree-based speculative decoding algorithm

w32zhong/tkblog

my blog.

w32zhong/toolformer-pytorch

Implementation of Toolformer, Language Models That Can Use Tools, by MetaAI

w32zhong/trl

Train transformer language models with reinforcement learning.

w32zhong/vivado-risc-v

Xilinx Vivado block designs for FPGA RISC-V SoC running Debian Linux distro

w32zhong/vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

w32zhong/webarena

Code repo for "WebArena: A Realistic Web Environment for Building Autonomous Agents"