C++ Actor Framework VS Thrust

CAF

I'd like to mention the native actor model implementation CAF, the C++ Actor Framework, and share some experiences. (Disclaimer: I've been developing on CAF in the past and have a good relationship with the creator.) CAF (1) provides native actors without an VM layer, (2) type-safe interfaces so that the compiler yells at you when a receiver cannot handle a message, and (3) transparent copy-on-write messaging so that you can still push stuff through pipelines and induce only copies only when a ref count is greater than one.

In our telemetry engine VAST, we've been using CAF successfully for several years for building a distributed system that always has a saturated write path. CAF provides a credit-based streaming abstraction as well, so that you can have backpressure across a chain of actors, making burst-induced OOM issues a blast from the past. You also get all the other benefits of actors, like linking and monitoring, to achieve well-defined failure semantics: either be up and running or collectively fail, but still allowing for local recovery—except for segfaults, this is where "native" has a disadvantage over VM-based actor models.

With CAF's network transparent runtime, a message ender doesn't need to know where receiver lives; the runtime either passes the message as COW pointer to the receiver or serializes it transparently. Other actor model runtimes support that as well, but I'm mentioning it because our experience showed that this is great value: we can can slice and dice our actors based on the deployment target, e.g., execute the application in one single process (e.g., for a beefy box) or wrap actors into single OS processes (e.g., when deploying on container auto-scalers).

The deep integration with the C++ type system allowed us to define very stable RPC-like interfaces. We're currently designing a pub/sub layer as alternate access path, because users are interested in tapping into streaming feeds selectively. This is not easy, because request-response and pub/sub are two ends of a spectrum, but it turns out we can support nicely with CAF.

Resources:

- CAF: https://github.com/actor-framework/actor-framework

- VAST: https://tenzir.github.io/vast/docs/understand-vast/actor-mod... (sorry for the incompleteness, we're in migration mode from the old docs, but this page is summarizing the benefits of CAF for us best)

- Good general actor model background: http://dist-prog-book.com/chapter/3/message-passing.html#why...

VAST is a flight recorder and security content execution engine. On the one hand, there exists a continuous stream of high-volume data sources (such as network telemetry as NetFlow, Zeek, Suricata, and endpoint telemetry). On the other hand, VAST processes needle-in-haystack queries to provide answers to questions like "has this threat been relevant to us 8 months ago?", and supports threat hunters with an interactive query capability to explore the data. From an engineering perspective, we focus especially on the separation of read and write path, concurrent message passing in an actor model runtime (CAF), and leveraging open standards, like Apache Arrow, to establish a high-bandwidth data plane for sharing data with downstream tooling. A flexible plugin API enables additional security-specific use cases on top, such as realtime matching of threat intelligence or mining of asset data for passive inventorization.

Technologies: Apache Arrow, Flatbuffers, C++ Actor Framework, Linux, Docker, Kubernetes

this is frankly starting to sound a lot like the ridiculous "blue bubbles" discourse.

AMD's products have generally failed to catch traction because their implementations are halfassed and buggy and incomplete (despite promising more features, these are often paper features or career-oriented development from now-departed developers). all of the same "developer B" stuff from openGL really applies to openCL as well.

http://richg42.blogspot.com/2014/05/the-truth-on-opengl-driv...

AMD has left a trail of abandoned code and disappointed developers in their wake. These two repos are the same thing for AMD's ecosystem and NVIDIA's ecosystem, how do you think the support story compares?

https://github.com/HSA-Libraries/Bolt

https://github.com/NVIDIA/thrust

in the last few years they have (once again) dumped everything and started over, ROCm supported essentially no consumer cards and rotated support rapidly even in the CDNA world. It offers no binary compatibility support story, it has to be compiled for specific chips within a generation, not even just "RDNA3" but "Navi 31 specifically". Etc etc. And nobody with consumer cards could access it until like, six months ago, and that still is only on windows, consumer cards are not even supported on linux (!).

https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...

This is on top of the actual problems that still remain, as geohot found out. Installing ROCm is a several-hour process that will involve debugging the platform just to get it to install, and then you will probably find that the actual code demos segfault when you run them.

AMD's development processes are not really open, and actual development is silo'd inside the company with quarterly code dumps outside. The current code is not guaranteed to run on the actual driver itself, they do not test it even in the supported configurations.

it hasn't got traction because it's a low-quality product and nobody can even access it and run it anyway.

For a higher level GPU interface, Thrust provides "standard library"-like functions that run in parallel on the GPU (Nvidia only)

For GPGPU, I like thrust. C++-idiomatic way of writing CUDA code, passing between host and device, etc.

Users should work with higher level primitives like tasks, parallel loops, asynchronous functions etc. Think TBB, Thrust, Taskflow, lparallel for CL, etc.