Search Results for "throughput" - Page 2
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Showing 89 open source projects for "throughput"
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1
SyncKit
Local-first collaboration SDK for React, Vue, and Svelte
...Synckit’s synchronization engine efficiently handles differential syncing — transferring only changed blocks rather than entire files — which reduces bandwidth usage and accelerates sync throughput. -
2
Wireit
Wireit upgrades your npm/pnpm/yarn scripts to make them smarter
...It persists caches between runs and across CI so identical steps don’t redo expensive tasks like bundling or type-checking. The system also serializes or parallelizes scripts based on dependencies to avoid race conditions while maximizing throughput. Because it integrates at the script layer, it works with any underlying tool—TypeScript, Rollup, Jest, or bespoke commands—while remaining transparent to developers. -
3
Scalatra
Tiny Scala high-performance, async web framework
Scalatra is a lightweight, high-performance micro web framework written in Scala, inspired by the Ruby framework Sinatra. Its goal is to provide a minimal but expressive foundation for building web applications or REST APIs in Scala without the verbosity or steep learning curve of larger frameworks. It supports asynchronous request handling, routing, filters, content negotiation, and easy integration with templating, JSON libraries, and other web middleware. Being unopinionated, it lets... -
4
dperf
DPDK based 100Gbps network performance and load testing software
dperf is a DPDK based 100Gbps network performance and load testing software. Based on DPDK, dperf can generate huge traffic with a single x86 server: tens of millions of HTTP CPS，hundreds of Gbps throughput and billions of concurrent connections. Provides detailed statistics and identify every packet loss. Support multiple scenarios. Load testing and stability testing for Layer 4 Load Balancer and other Layer 4 gateways. Network performance testing for servers on cloud. Performance test of network package processing capability for NIC and CPU. ... -
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5
Light-4J
A fast, lightweight and more productive microservices framework
...In 2014, I realized that the IT industry was moving from Monolithic to Microservices and from on-premise data centers to the public clouds. To reduce the production cost for my applications, I need to find a lightweight platform that has a small memory footprint, high throughput, and low latency in Java. Java EE and Spring/Spring Boot are too heavy to be considered. Other lightweight Java platforms all have different issues on the separation between the business logic and technical cross-cutting concerns. Moreover, they are not cloud-native or designed for container/cloud. -
6
Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level... -
7
Grafbase
The Grafbase GraphQL Federation Gateway
...By supporting GraphQL federation standards, the platform enables teams to combine multiple subgraphs or services into a unified schema that clients can query as a single endpoint. Grafbase is designed for large-scale production environments, emphasizing high throughput, low latency, and efficient resource usage through its Rust implementation. The system also includes tools for schema governance, API lifecycle management, and collaboration workflows, helping engineering teams safely evolve complex APIs over time. -
8
TensorStore
Library for reading and writing large multi-dimensional arrays
...Transactional semantics allow atomic updates and consistent snapshots, which is essential for large, shared datasets used by ML and scientific workflows. The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
9
Honggfuzz
Security oriented software fuzzer
honggfuzz is a general-purpose, high-performance fuzzer that mixes coverage feedback with practical crash triage to uncover memory-safety and logic bugs. It supports multiple fuzzing modes—stdin, file, and networking—so targets can be exercised the same way they run in production. Instrumentation via compiler hooks or hardware/perf counters guides mutations toward previously unseen edges, while persistent mode keeps the target process alive to amortize startup costs. The tool integrates... -
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10
Smallpond
A lightweight data processing framework built on DuckDB and 3FS
...Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. Because the storage layer (3FS) is optimized for random access and high throughput, smallpond can shuffle data, repartition, and manage intermediate results across nodes. -
11
Fastify
Fast and low overhead web framework, for Node.js
...Fastify ships with thoughtful defaults like structured logging via Pino and AJV for schema validation, and it has first-class TypeScript types. The result is a server stack that scales to high throughput while remaining easy to reason about in production. -
12
Isaac ROS Visual SLAM
Visual SLAM/odometry package based on NVIDIA-accelerated cuVSLAM
Discover a faster, easier way to build advanced AI robotics applications with the NVIDIA Isaac™ ROS collection of accelerated computing packages and AI models, bringing NVIDIA acceleration to ROS developers everywhere. Isaac ROS Visual SLAM provides a high-performance, best-in-class ROS 2 package for VSLAM (visual simultaneous localization and mapping). This package uses one or more stereo cameras and optionally an IMU to estimate odometry as an input to navigation. It is GPU-accelerated to... -
13
frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
14
Devtron
Tool integration platform for Kubernetes
...Provides deployment metrics like; deployment frequency, lead time, change failure rate, and mean-time recovery. Seamlessly integrates with Grafana for continuous application metrics like CPU and memory usage, status code, throughput, and latency on the dashboard. -
15
DALI
A GPU-accelerated library containing highly optimized building blocks
...DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. -
16
AutomatedLab
Framework that lets you deploy complex labs on HyperV and Azure
...There are only two requirements you need to make sure: You need the DVD ISO images and a Hyper-V host or an Azure subscription. Requires Windows Management Framework 5+ (Windows). Requires Intel VT-x or AMD/V capable CPU, a decent amount of RAM, and low-latency high-throughput storage (No spinning disks please, as there are issues related to them). This solution supports setting up virtual machines with Windows 7, 2008 R2, 8 / 8.1 and 2012 / 2012 R2, 10 / 2016, 2019, and SQL Server 2008, 2008R2, 2012, 2014, 2016, 2017, 2019. -
17
ElasticJob
Distributed scheduled job framework
...It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and efficiency improvement. Job processing capacity is flexible and scalable with the allocation of resources. Execute job on suitable time and assigned resources. Aggregation same job to same job executor. Append resources to newly assigned jobs dynamically. Using ElasticJob can make developers no longer worry about the non-functional requirements such as jobs scale out, so that they can focus more on business coding. -
18
Workerman
An asynchronous event driven PHP socket framework
...It has many high-performance components such as asynchronous Mysql, asynchronous Redis, asynchronous Http, MQTT Internet of Things client, and asynchronous message queue. Based on the high-performance Epoll event network library, a single machine can support millions of concurrent connections, with a long connection throughput of up to 36W/S. Objects such as PHP database can be resident in memory, reducing analysis and compilation and network overhead. -
19
XLS
XLS: Accelerated HW Synthesis
...XLS also provides tooling for pipelining, state insertion, and formal equivalence checks between different stages, giving developers confidence as designs evolve. The result is a productive path from high-level specification to real hardware, without giving up control over latency, throughput, and area trade-offs. -
20
Netty
An event-driven asynchronous network application framework
...It wraps Java NIO with a channel/handler pipeline model, enabling clean composition of codecs, TLS, and application logic with minimal overhead. Its ByteBuf abstractions, buffer pooling, and zero-copy techniques help reduce GC pressure and improve throughput under heavy I/O. Support for common protocols—HTTP/1.1, HTTP/2, WebSocket, and raw TCP/UDP—makes it a foundation for RPC frameworks, proxies, and messaging systems. Pluggable transports and native integrations (like epoll or kqueue where available) allow fine-tuning for different operating systems. With robust resource management, leak detection, and extensive testing, Netty is widely chosen when low latency, scalability, and control over the I/O stack are required. -
21
Lapis
A web framework for Lua and OpenResty written in MoonScript
...Have a look at Web Framework Benchmarks just to see how OpenResty stacks up against other platforms. Utilizing the power of Lua coroutines, you can write clean code that looks synchronous but can achieve high throughput by automatically running asynchronously without blocking. Networking operations like database queries and HTTP requests will automatically yield to allow for handling concurrent requests, all without all that callback spaghetti seen in other asynchronous platforms. -
22
Fluent Bit Plugin for CloudWatch Logs
A Fluent Bit output plugin for CloudWatch Logs
...To access sub-values in the map use the form $(variable['subkey']). Also, it can be replaced with special values to insert the tag, ECS metadata, or a random string in the name. It can achieve higher throughput and will consume less CPU and memory. -
23
JCTools
Java Concurrency Tools for the JVM
Java Concurrency Tools for the JVM. This project aims to offer some concurrent data structures currently missing from the JDK. There’s more to come and contributions/suggestions are most welcome. JCTools has enjoyed support from the community and contributions in the form of issues/tests/documentation/code have helped it grow. JCTools offers excellent performance at a reasonable price (FREE! under the Apache 2.0 License). It’s stable and in use by such distinguished frameworks as Netty,... -
24
Synapse Machine Learning
Simple and distributed Machine Learning
...With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster. -
25
HighwayHash
Fast strong hash functions: SipHash/HighwayHash
...It’s designed to defeat hash-flooding attacks by mixing input with wide SIMD operations and a branch-free inner loop, so adversaries can’t cheaply craft many colliding keys. The implementation targets multiple CPU families with vectorized code paths while keeping a portable fallback, yielding high throughput across platforms. It exposes simple one-shot and streaming APIs, so you can hash short keys or long byte streams with the same function. Typical uses include protecting hash tables that store untrusted keys and authenticating short-lived messages or records in storage systems. Although not a replacement for collision-resistant digests like SHA-2/3, it strikes a pragmatic balance of speed, simplicity, and resistance to common abuse patterns seen in production backends.
