Search Results for "throughput"
Sort By:
Showing 19 open source projects for "throughput"
View related business solutions-
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.
-
Streamline Azure Security with Palo Alto Networks VM-SeriesImprove your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
-
1
HikariCP
A solid, high-performance, JDBC connection pool at last
HikariCP is a high-performance JDBC connection pooling library designed to offer minimal overhead and maximum throughput. It aims for simplicity and stability, concentrating on fast connection acquisition and minimal latency under load. Its internals manage a pool of connections aggressively but smartly, with options such as leak detection, timeout thresholds, and adaptive connection retirement. Because it avoids heavy internal locking, it scales well in high-concurrency environments, making it a popular choice in microservices and high-throughput web backends. ... -
2
Napkin Math
Techniques and numbers for estimating system's performance
...It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as rounded numbers for reasoning rather than exact performance guarantees. The repository is especially useful for system design interviews, architecture planning, capacity estimation, and infrastructure cost discussions. ... -
3
DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. ... -
4
CoreNet
CoreNet: A library for training deep neural networks
...CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. ... -
6
Zeebe
Distributed Workflow Engine for Microservices Orchestration
Automate processes at scale with unprecedented performance and resilience. Zeebe is the workflow and decision engine that powers Camunda Platform 8. Zeebe’s cloud-native design provides the performance, resilience, and security enterprises need to future-proof their process orchestration efforts. Zeebe distributes data across all brokers in a cluster with storage directly on the server filesystem. If one broker goes down, another can replace it with no data loss. This pre-configured... -
7
Node RDKafka
Node.js bindings for librdkafka
A high-performance Node.js client for Apache Kafka, built on top of librdkafka, providing bindings for efficient Kafka message processing. -
8
Async MySQL Connector .NET and .NET Core
Async MySQL Connector for .NET and .NET Core
...This library implements true asynchronous I/O for database operations, without blocking (or using Task.Run to run synchronous methods on a background thread). This greatly improves the throughput of a web server that performs database operations. This library outperforms MySQL Connector/NET (MySql.Data) on benchmarks. This library is MIT-licensed and may be freely distributed with commercial software. Commercial software that uses Connector/NET may have to purchase a commercial license from Oracle. Fixes dozens of open bugs in Oracle’s Connector/NET; passes all ADO.NET Specification Tests. ... -
9
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. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
-
10
workerpool
Offload tasks to a pool of workers on node.js and in the browser
...It supports task queuing, dynamic worker scaling, timeouts, transferable objects, and proxy-based APIs for interacting with worker functions as if they were local calls. workerpool is designed to improve application responsiveness and throughput in workloads involving heavy computation, data processing, or asynchronous execution. The library works across multiple environments, supporting Web Workers in browsers and Worker Threads or child processes in Node.js. Its architecture emphasizes ease of integration, scalability, and efficient concurrency management for modern JavaScript applications. -
11
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. -
12
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... -
13
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. -
14
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. -
15
LMAX Disruptor
High performance inter-thread messaging library
LMAX aims to be the fastest trading platform in the world. Clearly, in order to achieve this we needed to do something special to achieve very low-latency and high-throughput with our Java platform. Performance testing showed that using queues to pass data between stages of the system was introducing latency, so we focused on optimising this area. The Disruptor is the result of our research and testing. We found that cache misses at the CPU-level, and locks requiring kernel arbitration are both extremely costly, so we created a framework which has "mechanical sympathy" for the hardware it’s running on, and that’s lock-free. ... -
16
Dragonboat
A feature complete and high performance multi-group Raft library in Go
...It also appears to clients as a single entity with strong data consistency always provided. All Raft replicas can be used to handle read requests for aggregated read throughput. Dragonboat handles all technical difficulties associated with Raft to allow users to just focus on their application domains. It is also very easy to use, our step-by-step examples can help new users to master it in half an hour. Easy to use pure-Go APIs for building Raft based applications. Feature complete and scalable multi-group Raft implementation. ... -
17
PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
PerfKitBenchmarker is an open-source benchmarking framework designed to measure and compare the performance of cloud infrastructure across multiple providers in a consistent and reproducible way. It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile for performance analysis. It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. ... -
18
Erlang Resource Pool
Resource Pool manages reusable resources among multiple processes.
...The goal of the tool is reduce the overhead of creating new resources by reusing of the same resources among multiple processes. Achieving result is better performance and throughput. The resource pool was inspired by Java Apache's commons pool and adopts API and main principals from this project. Database connection is most popular example for pooling resource. -
19
rmisockfactory
Collection of RMI Socket Factories
This project contains a collection of RMI socket factories -- for instance gzip-encoded data sent over the wire, NIO-based communication etc.
- Previous
- You're on page 1
- Next
