Luigi Cruz
@luigifcruz.bsky.social
Computer Engineer. Radio Amateur (PU2SPY). I talk about SDR, Raspberry Pi, Machine Learning, Parallel Computing, Satellites, Python, C++, and Golang.
Thanks to Fast Machine Learning Conference for inviting me to present our next-gen GPU-accelerated signal processing pipeline for radio astronomy!
Built with NVIDIA Holoscan + NEXUS orchestration for real-time processing across telescope arrays.
Slides: cdn.luigi.ltd/FastML.pdf
Built with NVIDIA Holoscan + NEXUS orchestration for real-time processing across telescope arrays.
Slides: cdn.luigi.ltd/FastML.pdf
September 3, 2025 at 7:10 PM
Thanks to Fast Machine Learning Conference for inviting me to present our next-gen GPU-accelerated signal processing pipeline for radio astronomy!
Built with NVIDIA Holoscan + NEXUS orchestration for real-time processing across telescope arrays.
Slides: cdn.luigi.ltd/FastML.pdf
Built with NVIDIA Holoscan + NEXUS orchestration for real-time processing across telescope arrays.
Slides: cdn.luigi.ltd/FastML.pdf
What workflows do you want to see supported by CyberEther? I’m planning the next five years of development!
August 31, 2025 at 4:27 AM
What workflows do you want to see supported by CyberEther? I’m planning the next five years of development!
Booting the Raspberry Pi 5 from an NVMe is satisfyingly quick! I enabled PCIe 3.0 x1 mode and it made it a few seconds faster.
August 2, 2025 at 7:07 PM
Booting the Raspberry Pi 5 from an NVMe is satisfyingly quick! I enabled PCIe 3.0 x1 mode and it made it a few seconds faster.
New Milestone: Our first validated Coyote server!
Packed into a 4U chassis:
- 192 GB of VRAM – 4x RTX 6000 Ada
- 16 TB NVMe storage
- 800 Gbps of networking
Powering the next-generation signal processing at the Allen Telescope Array. Designed for science, engineered for more!
Packed into a 4U chassis:
- 192 GB of VRAM – 4x RTX 6000 Ada
- 16 TB NVMe storage
- 800 Gbps of networking
Powering the next-generation signal processing at the Allen Telescope Array. Designed for science, engineered for more!
July 24, 2025 at 12:02 AM
New Milestone: Our first validated Coyote server!
Packed into a 4U chassis:
- 192 GB of VRAM – 4x RTX 6000 Ada
- 16 TB NVMe storage
- 800 Gbps of networking
Powering the next-generation signal processing at the Allen Telescope Array. Designed for science, engineered for more!
Packed into a 4U chassis:
- 192 GB of VRAM – 4x RTX 6000 Ada
- 16 TB NVMe storage
- 800 Gbps of networking
Powering the next-generation signal processing at the Allen Telescope Array. Designed for science, engineered for more!
Playing with CyberEther Python API (called Superluminal) inspired on Matplotlib for real-time visualizations!
Feeding it data straight from a CUDA signal generator built with NVIDIA Warp.
Here’s a similar demo: github.com/luigifcruz/C...
Feeding it data straight from a CUDA signal generator built with NVIDIA Warp.
Here’s a similar demo: github.com/luigifcruz/C...
July 13, 2025 at 5:18 AM
Playing with CyberEther Python API (called Superluminal) inspired on Matplotlib for real-time visualizations!
Feeding it data straight from a CUDA signal generator built with NVIDIA Warp.
Here’s a similar demo: github.com/luigifcruz/C...
Feeding it data straight from a CUDA signal generator built with NVIDIA Warp.
Here’s a similar demo: github.com/luigifcruz/C...
I might skip GNU Radio Conference this year as I’m not sure if my 4th CyberEther Yearly Update is going to be accepted. This breaks a three year old tradition at GRC but I’m hopeful to find other conferences to host it.
July 10, 2025 at 9:36 PM
I might skip GNU Radio Conference this year as I’m not sure if my 4th CyberEther Yearly Update is going to be accepted. This breaks a three year old tradition at GRC but I’m hopeful to find other conferences to host it.
I’m designing a modular baseboard for embedded projects: ESP32 or RP2350, power management, and a CM4-style board-to-board connector.
The idea is to swap in daughterboards for whatever function I need. No custom PCB every time. Here’s the schematic.
Any feedback before layout?
The idea is to swap in daughterboards for whatever function I need. No custom PCB every time. Here’s the schematic.
Any feedback before layout?
July 7, 2025 at 5:39 AM
I’m designing a modular baseboard for embedded projects: ESP32 or RP2350, power management, and a CM4-style board-to-board connector.
The idea is to swap in daughterboards for whatever function I need. No custom PCB every time. Here’s the schematic.
Any feedback before layout?
The idea is to swap in daughterboards for whatever function I need. No custom PCB every time. Here’s the schematic.
Any feedback before layout?
I’m testing a mini version of the server made for our next-generation signal processing pipeline. This handles 400G of data ingest, has 96 GB of VRAM with two RTX 6000 Ada, and up to 64TB NVMe. The full server has twice the capacity on the same 4U chassis. github.com/luigifcruz/s...
July 2, 2025 at 6:51 AM
I’m testing a mini version of the server made for our next-generation signal processing pipeline. This handles 400G of data ingest, has 96 GB of VRAM with two RTX 6000 Ada, and up to 64TB NVMe. The full server has twice the capacity on the same 4U chassis. github.com/luigifcruz/s...
I started committing code again to CyberEther after a hiatus. The main focus is to reach the Beta stage.
To a user means a lot more documentation, stability, and a complete high-level API for Python and C++ (Superluminal).
To a developer, easier render calls and a new kind of compute backend.
To a user means a lot more documentation, stability, and a complete high-level API for Python and C++ (Superluminal).
To a developer, easier render calls and a new kind of compute backend.
June 2, 2025 at 7:00 AM
I started committing code again to CyberEther after a hiatus. The main focus is to reach the Beta stage.
To a user means a lot more documentation, stability, and a complete high-level API for Python and C++ (Superluminal).
To a developer, easier render calls and a new kind of compute backend.
To a user means a lot more documentation, stability, and a complete high-level API for Python and C++ (Superluminal).
To a developer, easier render calls and a new kind of compute backend.
In this episode of “You Are Wrong, And Here’s Why”…
February 10, 2025 at 7:53 PM
In this episode of “You Are Wrong, And Here’s Why”…