* Version 0.5 is released. Except for various performance improvements, including spinlock, context switch,
and new run queue for coroutine scheduling, we have re-implemented the HTTP module so that there is no `boost` dependency anymore.
* Version 0.4 has come, bringing us these three major features:
1. Support coroutine local variables. Similar to the C++11 `thread_local` keyword. See [doc](doc/thread-local.md).
2. Support running on macOS platform, both Intel x86_64 and Apple M1 included.
3. Support LLVM Clang/Apple Clang/GCC compilers.
* Photon 0.3 was released on 2 Sep 2022. Except for bug fixes and improvements, a new `photon_std` namespace is added.
Developers can search for `std::thread`, `std::mutex` in their own projects, and replace them all into the equivalents of `photon_std::
Photon is well-suited for developing any I/O-intensive applications,
including those involving disk I/O and/or network I/O.
* **Performance** Photon can switch to a thread in just a few nanoseconds;
this action corresponds to callback in a typical asynchronous framework.
The cost of creating a new thread is primarily a simple malloc(),
and the allocation can be pooled for even greater efficiency.
Performance benchmarks on I/O workloads are available
[here](https://photonlibos.github.io/docs/category/performance).
* **Production** Photon is the foundation of many production systems in
(listing in alphabetical order)
[Alibaba Group](https://www.alibabagroup.com/en-US),
[Ant Group](https://www.antgroup.com/en),
[ByteDance](https://www.bytedance.com/en/),
[Xiaomi](https://www.mi.com/global/),
[XSKY](https://www.xsky.com/en/),
etc., and many open source projects in public domain.
* [overlaybd](https://github.com/containerd/overlaybd),
a sub-project of [containerd](https://containerd.io/), which is deployed
at scale in Alibaba's own infrastructure as well as the public cloud platform.
* [OSSFSv2](https://www.alibabacloud.com/help/en/oss/developer-reference/ossfs-2-0/),
a high-performance client for Alibaba Cloud's object storage service (OSS)
that provides a POSIX-compliant file system interface to the users.
* [Connector for AI/ML](https://github.com/aliyun/oss-connector-for-ai-ml),
a high-performance storage driver for popular AI frameworks, such as
Pythorch, safetensors, vllm, etc., supporting dataset reading, checkpointing,
model loading.
* [P2P Transport](https://www.alibabacloud.com/help/en/acr/use-the-p2p-acceleration-feature-in-ask-and-ack-clusters),
a key component that addresses the scalability issue of large scale data
serving, which is found in many scenarios like container image service, or
AI model loading, etc.
* Caching services, such as [OSS Accelerator](https://www.alibabacloud.com/help/en/oss/overview-77/),
a multi-tenant distributed caching service for high-performance object access;
or [EFC cache](https://www.alibabacloud.com/help/en/nas/user-guide/enable-the-distributed-caching-feature-of-the-cnfs-client),
a client-side caching module for elastic file client (EFC).
* [KTransformers](https://kvcache-ai.github.io/ktransformers/),
a flexible, Python-centric AI framework with advanced kernel optimizations
and placement/parallelism strategies, designed with extensibility at its core.
Photon is [used](https://github.com/alibaba/PhotonLibOS/issues/642) to
asynchronously load kvcache data from disk to memory, or vice versa.
* [The coroutine engine in VLang](https://github.com/vlang/v/blob/bfee8248603cfbe4022de8364260133f90d1783b/vlib/coroutines/README.md)
* **Agility** Photon is designed to support a wide range of applications —
and is already deployed in production across diverse environments. We’ve
gone beyond mere feasibility, engineering it to be not only highly adaptable,
but also intuitive, convenient, and fast to use. This is made possible
through a set of well-defined, modular abstractions that decouple core
logic from underlying system specifics, enabling both flexibility and
performance.
* **Portability** Photon supports multiple platforms, i.e. the
combinations of {Linux, macOS} * {x86_64, ARM64} * {gcc, clang}.
* **Inclusion** in [awesome-cpp](https://github.com/fffaraz/awesome-cpp)
## Community