Search Results for "memory" - Page 31
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Showing 2497 open source projects for "memory"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Engram
A New Axis of Sparsity for Large Language Models
...It provides utilities to generate embeddings from text or other structured data, index them using efficient approximate nearest neighbor algorithms, and perform real-time similarity queries even on large corpora. Engineered with speed and memory efficiency in mind, Engram supports batched indexing, incremental updates, and custom distance metrics so developers can tailor search behaviors to their domain’s needs. In addition to raw similarity search, the project includes tools for clustering, ranking, and filtering results, enabling richer user experiences like “related content”, semantic auto-completion, and contextual filtering. -
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NovaSR
A lightning fast audio upsampler
...NovaSR is especially valuable for post-processing tasks in speech enhancement, TTS pipelines, and dataset restoration where low sampling rates degrade perceived audio clarity; the minimal model size also makes it suitable for edge and embedded use cases where memory is at a premium. Its performance can reach thousands of times realtime on modern GPUs, allowing massive audio batches to be processed with negligible compute overhead. -
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Z80-μLM
Z80-μLM is a 2-bit quantized language model
...The project sits at the intersection of machine learning and systems constraints, showing how model architecture, quantization, and inference code generation can be adapted to extreme memory and compute limits. It also functions as an educational reference for how to reduce inference to operations that fit an old-school instruction set and runtime environment. -
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EC2Instances.info
Amazon EC2 instance comparison site
ec2instances is an open-source project that powers an intuitive, searchable comparison site for Amazon EC2 instance types, helping developers and cloud architects quickly evaluate compute options without the friction of navigating multiple AWS console screens. The site aggregates key metrics — including CPU, memory, storage, networking specs, and pricing — across many instance families, and lets users filter, sort, and visually compare configurations side by side. It was created to simplify decision-making for cloud provisioning, making it easier to choose the best instance type for performance and cost goals, and it’s maintained by the Vantage community to stay updated with current AWS offerings and user suggestions. ... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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Swift Guide
Swift Featured Projects in brain Mapping
SwiftGuide is a comprehensive, community-maintained guide to the Swift programming language, designed to serve as both a learning resource and a handy reference. It covers all major language aspects: syntax, control flow, functions, closures, generics, protocols, extensions, memory management, concurrency, and the standard library. Each topic typically includes clear explanations, annotated code snippets, and tips for best practices, helping readers understand both how features work and how to use them idiomatically. Over time, the guide has evolved alongside Swift itself, with updates to reflect new language releases, deprecations, and shifting patterns. ... -
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JMH Gradle Plugin
Integrates the JMH benchmarking framework with Gradle
...This reduces the manual effort of setting up JMH, making performance testing a natural part of the development cycle. The plugin is especially useful in projects where regression in execution speed or memory use must be carefully monitored. -
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Barter
Open-source Rust framework for building event-driven systems
Barter is an open-source, Rust-based ecosystem of libraries for building high-performance, event-driven algorithmic trading systems—covering live trading, paper trading, and backtesting. It is designed for safety, speed, and flexibility in quantitative finance workflows. Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. Centralised cache-friendly state management system with O(1) constant lookups using indexed data... -
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Monitorix
Monitorix is a free, open source, lightweight system monitoring tool
Monitorix is a free, open source, lightweight system monitoring tool designed to monitor as many services and system resources as possible. It has been created to be used under production Linux/UNIX servers, but due to its simplicity and small size can be used on embedded devices as well. It consists mainly of two programs: a collector, called monitorix, which is a Perl daemon that is started automatically like any other system service, and a CGI script called monitorix.cgi. Monitorix... -
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pgstream
PostgreSQL replication with DDL changes
pgstream is an open source CDC command-line tool and library that offers Postgres replication support with DDL changes to any provided output. One of the main differentiators of pgstream is the fact that it tracks and replicates schema changes automatically. It relies on SQL triggers that will populate a Postgres table (pgstream.schema_log) containing a history log of all DDL changes for a given schema. Whenever a schema change occurs, this trigger creates a new row in the schema log table... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so many more. ... -
11
Spice.ai OSS
A self-hostable CDN for databases
...Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. Accelerated engines give you flexibility and control over query cost and performance. -
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lua-resty-openidc
OpenID Connect Relying Party and OAuth 2.0 Resource Server
...It maintains sessions for authenticated users by leveraging lua-resty-session thus offering a configurable choice between storing the session state in a client-side browser cookie or use in of the server-side storage mechanisms shared-memory|memcache|redis. -
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Android Contacts, Reborn
Android Contacts API Library written in Kotlin
This library provides a complete set of APIs to do everything you need with Contacts in Android. You no longer have to deal with the Contacts Provider, database operations, and cursors. Whether you just need to get all or some Contacts for a small part of your app (written in Kotlin or Java), or you are looking to create your own full-fledged Contacts app with the same capabilities as the AOSP Android Contacts app and Google Contacts app, this library is for you. -
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kotlinx-io
Kotlin multiplatform I/O library
...Depending on the target platform, extension functions allowing data exchange with platform-specific types are also available. A Buffer consists of segments organized as a linked list: segments allow reducing memory allocations during the buffer's expansion and copy, with the latter achieved by delegating or sharing the ownership over the underlying buffer's segments with other buffers. -
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simdjson
Parsing gigabytes of JSON per second
JSON is everywhere on the Internet. Servers spend a *lot* of time parsing it. We need a fresh approach. The simdjson library uses commonly available SIMD instructions and microparallel algorithms to parse JSON 4x faster than RapidJSON and 25x faster than JSON for Modern C++. The simdjson library uses three-quarters less instructions than state-of-the-art parser RapidJSON. To our knowledge, simdjson is the first fully-validating JSON parser to run at gigabytes per second (GB/s) on commodity... -
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Quantum++
Modern C++ quantum computing library
...The main design factors taken in consideration were ease of use, high portability, and high performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast. -
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pgvecto.rs
Vector database plugin for Postgres, written in Rust
pgvecto.rs is a Postgres extension that provides vector similarity search functions. It is written in Rust and based on pgrx. It is currently under heavy development, please take care when using it in production. pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications. pgvecto.rs supports filtering. You can set conditions when searching or retrieving points. This... -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
...Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning. -
19
Mill
Your shiny new Java/Scala build tool
...These range from tiny unit tests, to larger integration tests that instantiate a TestUtil.BaseModule in-process and a TestEvaluator to evaluate tasks on it. Note that the in-memory tests compile the BaseModule together with the test suite, and do not exercise the Mill script-file bootstrapping, transformation, and compilation process. -
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Cache
Nothing but Cache
Cache doesn't claim to be unique in this area, but it's not another monster library that gives you a god's power. It does nothing but caching, but it does it well. It offers a good public API with out-of-box implementations and great customization possibilities. Cache utilizes Codable in Swift 4 to perform serialization. The cache is built based on a Chain-of-responsibility pattern, in which there are many processing objects, each knows how to do 1 task and delegates to the next one, so can... -
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http4k
The Functional toolkit for Kotlin HTTP applications
http4k is a lightweight but fully-featured HTTP toolkit written in pure Kotlin that enables the serving and consuming of HTTP services in a functional and consistent way. http4k applications are just Kotlin functions. http4k consists of a lightweight core library, http4k-core, providing a base HTTP implementation and Server/Client implementations based on the JDK classes. Further servers, clients, serverless, templating, websockets capabilities are then implemented in add-on modules. http4k... -
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go-linq
.NET LINQ capabilities in Go
...Supports arrays, slices, maps, strings, channels and custom collections. go-linq has recently introduced breaking API changes with v2.0.0. See release notes for details. v2.0.0 comes with a refined interface, dramatically increased performance and memory efficiency, and new features such as lazy evaluation. Although Go doesn't implement generics, with some reflection tricks, you can use go-linq without typing interface{}s and type assertions. This will introduce a performance penalty (5x-10x slower) but will yield in a cleaner and more readable code. -
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Casbin
An authorization library that supports access control models
...In Casbin, an access control model is abstracted into a CONF file based on the PERM metamodel (Policy, Effect, Request, Matchers). So switching or upgrading the authorization mechanism for a project is just as simple as modifying a configuration. Besides memory and file, Casbin policy can be stored into lots of places. Currently, dozens of databases are supported, from MySQL, Postgres, Oracle to MongoDB, Redis, Cassandra, AWS S3. Check the full supported list at: adapters. Casbin is implemented in Golang, Java, PHP and Node.js. All implementations share the same API and behaviors. You can learn Casbin once and use it everywhere. ... -
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PHP-Casbin
An authorization library that supports access control models
...In Casbin, an access control model is abstracted into a CONF file based on the PERM metamodel (Policy, Effect, Request, Matchers). So switching or upgrading the authorization mechanism for a project is just as simple as modifying a configuration. Besides memory and file, Casbin policy can be stored into lots of places. Currently, dozens of databases are supported, from MySQL, Postgres, Oracle to MongoDB, Redis, Cassandra, AWS S3. Check the full supported list at: adapters. Casbin is implemented in Golang, Java, PHP and Node.js. All implementations share the same API and behaviors. You can learn Casbin once and use it everywhere. -
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observer_cli
Visualize Erlang/Elixir Nodes On The Command Line
...Increments are values that are mostly useful when compared to a previous one to have an idea of what they're doing because otherwise, they'd never stop increasing: bytes in and out of the node, number of garbage collector runs, words of memory that were garbage collected, and the global reductions count for the node. Total scheduler utilization will equal 1.0 when all schedulers have been active all the time between the two refresh intervals. The result being that there is a decent chunk of CPU usage that would be mostly free for scheduling actual Erlang work (assuming the schedulers are busy waiting more than trying to select tasks to run).
