470 skills found · Page 8 of 16
witmemtech / CIM Technical Papers CollectionComputing in memory optimizes data handling by performing operations directly in memory, ideal for high-speed data processing needs. This compilation highlights its technologies and applications, offering a concise overview for professionals in the field.
bytedance / Eurosys24 ArtifactsArtifacts of EuroSys'24 paper "Exploring Performance and Cost Optimization with ASIC-Based CXL Memory"
Rexamm1t / NextRAMNextRAM - advanced memory optimization for Android - ZRAM, swap management, kernel tuning, AI optimization
dtouzeau / Proxmox OptimizerA comprehensive optimization tool specifically designed for Linux virtual machines running on Proxmox VE. This tool automatically detects your system configuration and applies optimal settings for memory management, disk I/O, network performance, and Proxmox-specific features.
Cre4T3Tiv3 / Unsloth Llama3 Alpaca LoraCustom model training using modern architectures. 4-bit QLoRA fine-tuning pipeline for LLaMA 3 8B with production-grade optimization. Memory-efficient training on consumer GPUs. Published adapter on HuggingFace. From training pipeline to deployed model.
Pfzuo / Path HashingA Write-friendly and Cache-optimized Hashing Scheme for Non-volatile Memory Systems (MSST 2017, TPDS 2018)
RainBlock / Merkle Patricia Tree☔️🌲 A fast, in-memory optimized merkle patricia tree
teleprint-me / Py.gpt.promptPyGPTPrompt: A CLI tool that manages context windows for AI models, facilitating user interaction and data ingestion for optimized long-term memory and task automation.
vertexclique / CuneiformCache & In-Memory optimizations for Rust, revived from the slabs of Sumer.
AngeloJacobo / FPGA SDRAM ControllerSDRAM controller optimized to a memory bandwidth of 316MB/s
jecsham / Shorthash2Mainly based on shorthash (apparently abandoned), by Bibig, shorthash2 offers a small optimization in memory usage, small features and is available for Browser and NodeJs.
applitopia / Immutable SortedThis is an extension of Immutable.js that provides sorted collections SortedMap and SortedSet. The current implementation is using highly optimized B-tree memory structure.
hyoseokp / PRISMPRISM: O(1) Photonic Block Selection for Long-Context LLM Inference — eliminates the O(N) KV cache scan via photonic broadcast-and-weight similarity engine on TFLN
cnsdqd-dyb / Guide GRPOAims for memory-efficient training (24GB VRAM) on consumer GPUs. Optimizing language models through guidance tokens in reasoning chains, based on DeepSeekRL-Extended.
gavinlyonsrepo / FourteenSegDisplayAn Arduino library to display data on a seven 7, nine 9, fourteen 14 or sixteen 16 segment alphanumeric LED display module. Will work with common anode and cathode. Includes ASCII font and supports Hexadecimal, Decimal point, strings. Optimized low memory footprint. Provides a function for manually setting segments to any pattern. Uses Shift registers
Bihaqo / Tf MemongerSublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets
KULeuven-MICAS / Zigzag ImcHW accelerator mapping optimization framework for in-memory computing
dipankarsk / Feature Selection HybridIntrusion Detection is a technique to identify the abnormal behavior of system due to attack. The unusual behavior of the environment is then identified and steps are taken and methods are formed to classify and recognize attacks. Data set containing a number of records sometimes may decrease the classifiers performance due to redundancy of data. The other problems may include memory requirements and processing power so we need to either reduce the number of data or the number of records. Feature Selection techniques are used to reduce the vertical largeness of data set. This project makes a comparative study of Particle Swarm Optimization, Genetic Algorithm and a hybrid of the two where we see that PSO being simpler swarm algorithm works for feature selection problems but since it is problem dependent and more over its stochastic approach makes it less efficient in terms of error reduction compared to GA. In standard PSO, the non-oscillatory route can quickly cause a particle to stagnate and also it may prematurely converge on sub optimal solutions that are not even guaranteed to be local optimum. A further drawback is that stochastic approaches have problem-dependent performance. This dependency usually results from the parameter settings in each algorithm. The different parameter settings for a stochastic search algorithm result in high performance variances. In this project the modification strategies are proposed in PSO using GA. Experimental results show that GA performs better than PSO for the feature selection in terms of error reduction problems whereas hybrid outperforms both the model in terms of error reduction.
cla7aye15I4nd / ShadowboundShadowBound: Efficient Memory Protection through Advanced Metadata Management and Customized Compiler Optimization (USENIX Security 2024) ✨
The-HaiKaw-Pr0tocol / MemoraDBMemoraDB is a high-performance in-memory database (IMDB) designed for ultra-low latency key-value storage and operations, featuring RESP protocol compliance, atomic commands, and TTL-based expiry. Optimized for microsecond response times, it's ideal for real-time applications like caching and session stores.
