6 个仓库
Specialized high-performance processing of multi-dimensional arrays and tensors.
Distinct from High-Performance Computing: Distinct from general High-Performance Computing: focuses specifically on the processing of array structures rather than distributed task scheduling.
Explore 6 awesome GitHub repositories matching scientific & mathematical computing · Array Processing. Refine with filters or upvote what's useful.
CuPy 是一个 CUDA 数组计算库,实现了与 NumPy 兼容的接口,用于在 NVIDIA GPU 上执行数组操作和数值计算。它作为一个 GPU 加速数值库和基于 CUDA 的 SciPy 实现,将繁重的计算卸载到图形硬件上,以提高科学和工程工作负载的处理速度。 该库支持多框架张量交换,允许使用标准化的内存布局在不同的深度学习框架之间共享数据缓冲区,从而避免内存拷贝。它还支持自定义 GPU 内核集成,允许将数组数据连接到低级 API,以便精确控制硬件执行。 该项目广泛涵盖了高性能数组处理和科学计算工作流。其功能包括加速数组计算和提供大规模数值计算工具。
Implements high-performance array processing by running NumPy and SciPy style operations on GPUs.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Improves performance by processing multiple rows simultaneously using array-based batching instead of individual values.
This repository is a comprehensive sample library providing reference implementations for automating tasks and extending functionality across Google Workspace applications. It serves as a collection of code examples and templates for building workspace automation scripts, custom add-ons, and integrated productivity tools. The project distinguishes itself by providing specialized examples for integrating large language models into productivity tools for content generation and data analysis. It also includes reference implementations for creating conversational chat apps, interactive cards, and
Minimizes server requests by using two-dimensional arrays for bulk data operations in spreadsheets.
Promptify 是一套专为模型评估、提示词管理、Token 成本跟踪、结构化提取和统一 API 网关访问而设计的工具。它提供了一个标准化接口,用于管理跨多个大型语言模型提供商的请求和响应。 该项目具有一个提示词管理平台,用于工程化和版本化带有结构化输出验证的提示词。它包括一个专门的评估框架,用于根据标记数据集测量模型性能(使用精确率、召回率和 F1 分数),以及一个 Token 成本跟踪器来监控模型请求的财务支出。 该库涵盖了自然语言处理的广泛功能,包括命名实体提取、文本分类和问答。它通过异步批处理支持高容量工作流,并通过模式验证将非结构化文本转换为类型化数据结构,从而确保数据一致性。
Supports high-volume workflows through asynchronous batch processing of multiple inputs to increase total throughput.
本项目是一个针对 Ruby on Rails 的静态分析工具和 Linter,旨在识别架构异味和最佳实践违规。它充当 Rails 应用的代码质量 Linter、架构审计员、安全扫描器和性能分析器。 该工具评估控制器、模型和视图模板之间的关注点分离,以减少技术债务。它识别次优的编码模式并强制执行风格一致性,同时专门扫描安全漏洞,如模型中未受保护的批量赋值。 分析范围涵盖检测低效的数据库查询和内存密集型数据检索模式。它还审计路由设计、验证记录持久化,并识别不当的错误处理和时区配置错误。 用户可以通过配置文件定义要启用或禁用的代码检查来管理分析。
Processes large datasets in chunks to prevent memory exhaustion during data retrieval.
Accelerate is a framework for high-performance array computing that provides a domain-specific language for expressing complex mathematical and parallel computations. By utilizing a declarative programming interface, it allows users to define high-level array transformations that are automatically translated into optimized machine code for diverse hardware architectures. The system distinguishes itself through a modular architecture that decouples high-level array operations from hardware-specific instructions. It employs just-in-time compilation and kernel fusion to transform programs into e
Provides a domain-specific language for expressing complex array computations that compile into optimized machine code for parallel hardware.