Search Results for "distributed shared memory"
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15 projects for "distributed shared memory" with 2 filters applied:
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JetCache
JetCache is a Java cache framework
...It provides more powerful annotations than those in Spring Cache. The annotations in JetCache support native TTL, two-level caching, and automatically refresh in distributed environments, also you can manipulate Cache instances by your code. Currently, there are four implementations: RedisCache, TairCache(not open source on github), CaffeineCache (in memory) and a simple LinkedHashMapCache (in memory). -
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Holochain
The current, performant & industrial strength version of Holochain
Holochain is a post-blockchain framework for building agent-centric, distributed applications. Instead of using global consensus, Holochain enables each agent (user) to maintain their own local state while validating actions with a shared set of rules. This allows for scalable, secure, and resilient apps where data is owned and controlled by users. Ideal for social apps, cooperatives, and data sovereignty platforms, Holochain focuses on enabling collaboration without central servers or miners. ... -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. ... -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express... -
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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... -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. ... -
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Light-4J
A fast, lightweight and more productive microservices framework
Light means lightweight, lightning-fast and shedding light on how to program with modern Java SE for cloud-native deployment. I had been working on the Java EE platforms since early 2000 and suffered performance and productivity issues. 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... -
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Laravel Haystack
Supercharged job chains for Laravel
Laravel Haystack provides supercharged job chains for Laravel. It comes with powerful features like delaying jobs for as long as you like, applying middleware to every job, sharing data and models between jobs and even chunking jobs. Laravel Haystack supports every queue connection/worker out of the box. (Database, Redis/Horizon, SQS). It's great if you need to queue thousands of jobs in a chain or if you are looking for features that the original Bus chain doesn't provide. If you need to... -
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EasyZSwoole
swoole, easyswoole, swoole framework
EasySwoole is a distributed swoole framework with a permanent memory. It is born specifically for API and supports the simultaneous monitoring of HTTP, WebSocket, self-defined TCP, UDP protocol, and has rich components, such as collaboration Connect Pool, TP style co-process ORM, co-process microcredit SDK, co-process Kafka client, co-process ElasticSearch client, co-process Consul client, co-process Redis client, co-process Apollo client, co-process NSQ client, co-process self-definition queue、 Many components such as the Memcached client, the co-process view engine, JWT, the co-process RPC, the co-process SMTP client, the co-process HTTP client, the co-process Actor, and the Crontab timer. ... -
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Rocket Chip
Rocket Chip Generator
...A diplomacy framework (LazyModules) lets designers wire components with negotiated parameters, enabling reuse and rapid exploration of different cache sizes, port counts, and memory hierarchies. The generator supports custom accelerators through the RoCC interface, allowing domain-specific compute units to be plugged into the pipeline with shared cache and memory semantics. Tooling integrates with FIRRTL, Verilator, and commercial EDA flows, and the ecosystem around Rocket Chip (e.g., Chipyard) adds harnesses, peripherals, and verification infrastructure. -
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As of now, you can get Ehcache only from ehcache.org or Maven central. A simple, fast, thread safe, standards based cache for Java, and provides memory and disk stores and distributed operation for clusters. ehcache is widely used in such open source projects as Hibernate and Spring. Terracotta offers enterprise edition
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Tuple Spaces
Tuple space with time outs and transactions.
Java implementation of a Tuplespace. Moved to https://github.com/mike-k-houghton/tuplespace A Tuple is an ordered list of items. A Tuple Space is a form of associative memory where entries, tuples, are stored in the space and are retrieved using search criteria that are based on the intrinsic properties of the tuples. The two key operations are put get And that is it! There are refinements on these operations including, for example, timeouts where the tuple will only exist... -
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Channel is a C++ framework for distributed message passing and event dispatching, configurable with its components (msg ids,routing algorithms...) as template parameters. As a namespace shared by peer threads, channel supports scope control and filtering
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Library that offers users an easy to use interface to synchronize shared data access following the software transactional memory principle.
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QuickMP (Quick Multi-Processing) is a simple cross-platform C++ API for generating parallel for loops in shared-memory programs, similar to OpenMP. It provides automatic scalable performance based on the number of available processors.
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