Search Results for "server performance"
Sort By:
Showing 9 open source projects for "server performance"
View related business solutions-
Earn up to 16% annual interest with Nexo.Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
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.
-
1
OpenVINO Model Server
A scalable inference server for models optimized with OpenVINO
OpenVINO™ Model Server is a high-performance inference serving system designed to host and serve machine learning models that have been optimized with the OpenVINO toolkit. It’s implemented in C++ for scalability and efficiency, making it suitable for both edge and cloud deployments where inference workloads must be reliable and high throughput. The server exposes model inference via standard network protocols like REST and gRPC, allowing any client that speaks those protocols to request predictions remotely, abstracting away the complexity of where and how the model runs. ... -
2
Zvec
A lightweight, lightning-fast, in-process vector database
...Its performance benchmarks show it achieving high queries-per-second and fast index build times compared to similar tools. Because it runs in-process, developers can embed it in native apps, microservices, or edge computing scenarios where traditional server-based vector databases might be overkill. -
3
NVIDIA cuOpt
GPU accelerated decision optimization
...Built primarily in C++, cuOpt leverages NVIDIA GPUs to deliver near real-time solutions for optimization tasks involving millions of variables and constraints. The platform provides multiple interfaces, including C, Python, and server APIs, allowing developers to integrate optimization capabilities into applications and services. cuOpt is designed for high-performance environments and can be deployed across cloud, hybrid, or on-premise infrastructures. By combining GPU acceleration with scalable APIs, cuOpt enables organizations to solve large optimization challenges in logistics, operations research, and decision-making systems. -
4
PowerInfer
High-speed Large Language Model Serving for Local Deployment
...PowerInfer incorporates specialized algorithms and sparse operators to manage neuron activation patterns and minimize data transfers between hardware components. As a result, it enables powerful language models to run on consumer hardware while achieving performance comparable to more expensive server-grade systems. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
5
TensorFlow
TensorFlow is an open source library for machine learning
...Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended. -
6
llama.cpp
LLM inference in C/C++
llama.cpp is a high-performance C and C++ project for running large language models locally and in the cloud with minimal setup. It is built around efficient inference, broad hardware support, and the GGUF model format. The project supports many model families and has become a major foundation for local AI tools, model serving, and embedded inference workflows. -
7
bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
8
OceanBase seekdb
The AI-Native Search Database
seekdb is an AI-native search database from OceanBase that unifies vector, full-text, relational, JSON, and GIS data into a single query engine. The system is designed to support hybrid search workloads and in-database AI workflows without requiring multiple specialized databases. It enables developers to perform semantic search, keyword search, and structured SQL queries within the same platform, simplifying modern AI application stacks. seekdb also embeds AI capabilities directly in the... -
9
TerarkDB
A RocksDB compatible KV storage engine with better performance
TerarkDB is an open-source storage engine designed as a replacement for RocksDB — offering improved performance, better compression, and optimized tail-latency for key-value workloads. It aims to be drop-in compatible with existing RocksDB setups: you can migrate most RocksDB instances over to TerarkDB without rewriting your storage logic. Under the hood, TerarkDB employs advanced data structures and compression strategies to reduce I/O, memory usage, and latency variability — delivering... -
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.
- Previous
- You're on page 1
- Next
