Search Results for "performance"
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38 projects for "performance" with 2 filters applied:
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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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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ngraph.path
Path finding in a graph
...It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. Its data structures and algorithm choices are optimized for performance and memory efficiency, so even large meshes or road networks can be navigated interactively. ... -
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The Algorithms Python
All Algorithms implemented in Python
...It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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DeepSpec
A full-stack codebase for training and evaluating speculative decoding
...The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline measures speculative decoding performance across benchmark tasks such as math, coding, instruction-following, and chat-style datasets. Overall, it is useful for researchers and engineers studying faster language model inference through speculative decoding methods. -
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YAPF
A formatter for Python files
YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide. You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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trackers
Multi-object tracking algorithms
...It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that include labels and trajectories. Trackers is built for flexibility and benchmarking, allowing users to evaluate performance using standard multi-object tracking metrics and compare algorithms easily. Its architecture emphasizes interoperability so developers can combine their preferred detection models with different trackers without rewriting core logic. -
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javascript-algorithms
JavaScript implementations of computer science algorithms
javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts.... -
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...Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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The ASCO project aims to bring circuit optimization capabilities to existing SPICE simulators using a high-performance parallel differential evolution (DE) optimization algorithm. It supports Eldo, HSPICE, LTspice, Spectre, and Qucs.
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
...Because Reptile is a first-order algorithm, it avoids computing second derivatives or full meta-gradients, making it computationally simpler while retaining good performance. The repo includes training scripts, dataset fetchers (Omniglot, Mini-ImageNet), and modules for defining the Reptile update logic, variables, and hyperparameters. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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AhoCorasickDoubleArrayTrie
An extremely fast implementation of Aho Corasick algorithm
...The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. In short, it’s a specialized, speed-focused library for industrial-strength multi-keyword matching in Java. -
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React Fiber Architecture
A description of React's new core algorithm, React Fiber
...It also introduces the concept of fibers as data structures representing units of work that can be paused, resumed, or reused. The project is especially valuable for developers who want to understand React’s performance model and concurrency features at a low level. -
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Algorithms in Python
Data Structures and Algorithms in Python
...Because it’s openly maintained, you can browse through issues, see test cases, and observe coding style in a “learning through code” fashion. It also serves as a playground where you can add problems, measure performance, and compare different algorithmic approaches. For anyone striving to move from “I know the syntax” to “I know how to use the right algorithm at the right time,” this repository is a practical asset. -
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TommyDS is a C library of hashtables and tries designed for high performance.
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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SWAPHI-LS: Alignment on Xeon Phi Cluster
Smith-Waterman long DNA sequence alignment on Xeon Phi clusters
The first parallel Smith-Waterman algorithm exploiting Intel Xeon Phi clusters to accelerate the alignment of long DNA sequences. This algorithm is written in C++ (with a set of SIMD intrinsic extensions), OpenMP and MPI. The performance evaluation revealed that our algorithm achieves very stable performance, and yields a performance of up to 30.1 GCUPS on a single Xeon Phi and up to 111.4 GCUPS on four Xeon Phis sharing a host. -
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DJVU++
The DjVu complete solution,with OCR Technology(Arabic ,English).
...o DjVu++ supports multiple formats: Convert PDF document into DjVu format with smaller file size and the same performance. Convert DjVu into PDF format. Combine images to a single DjVu document. Perform OCR operations on multiple image formats. -
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CUSHAW2: Parallel Gapped Read Alignment
One of the leading short-/long-read aligner to large genomes
CUSHAW2 is a fast and parallel gapped read alignment to large genomes, such as the human genome. The performance evaluation, by aligning simulated and real datasets to the human genome, shows that CUSHAW2 is consistently among the highest-ranked aligners in terms of alignment quality for both single-end and paired-end alignment, while demonstrating highly competitive speed. Furthermore, our aligner shows good parallel scalability with respect to the number of CPU threads. -
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JBernstein
JBernstein: Exploration techniques for non-linear constraint checking
...The underlying algorithm is based on a translation to Bernstein polynomials, and several optimization techniques are implemented to ensure efficiency. Concerning performance, the tool enables to check all examples in the PVS Bernstein testsuite within a second, which can be an order of magnitude faster than some other tools such as QEPCAD or REDLOG. Although JBernstein uses double, it offers automatic error-estimation capabilities (experimental) so that the generated result is correct (the solver may return unknown when the error-estimate is too large) -
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Funnel Sort
command line sort utility
Moved to GitHub https://github.com/fedups A command-line utility to sort files. Funnel is a sort utility to sort files, large and small. It efficiently handles fixed length records and variable length records. Funnel easily handles ascii (readable) data and binary data. There are many more features in Funnel. It is easy to use and very fast. All documentation is on the Wiki. -
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...We present a Chase & Backchase (C&B) algorithm strategy that generalizes and improves on well-known methods in the field. The implementation of our approach, the pegasus system, outperforms existing C&B systems an average by two orders of magnitude. This gain in performance is due to a combination of novel methods that lower the complexity in practical situations significantly.
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parFE is fully-parallel high-performance finite element code targeted to the modeling of trabecular bones in humans. It employs scalable multigrid solvers for efficient solutions on massively parallel computers.
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...It contains implementation of the most important computational geometry data structures and algorithms coded in pure Java, designed for ease of use and optimized for performance.
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Libface is a cross platform framework for developing face recognition algorithms and testing its performance.
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Lightweight prime number generation library. Makes use of OpenMP and aims for performance. Suitable for applications in cryptography or just for educational demonstration.
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libconhash is a consistent hashing libraray, which can be compiled both on Windows and Linux platform. High performance, easy to use, and easy to scale according to node's processing capacity.
