Alternatives
Products that do what Volume Shader does
Gpu benchmark test tool
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Volume Shader - The Ultimate 3D GPU Benchmark & Stress Test
Jan 2026 · volumeshader.pro
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Test your GPU performance instantly in your browser
Apr 2026 · devicexa.com
- 3CW
Creator here. I built ChartGPU because I kept hitting the same wall: charting libraries that claim to be "fast" but choke past 100K data points. The core insight: Canvas2D is fundamentally CPU-bound. Even WebGL chart libraries still do most computation on the CPU. So I moved everything to the GPU via WebGPU: - LTTB downsampling runs as a compute shader - Hit-testing for tooltips/hover is GPU-accelerated - Rendering uses instanced draws (one draw call per series) The result: 1M points at 60fps with smooth zoom/pan. Live demo:…
Jan 2026 · github.com
- 4AR
I’ve been experimenting with Rust lately and wanted a project that would help me explore some of its lower-level and performance-oriented features. Inspired by Sebastian Lague’s videos, I decided to implement my own ray tracer from scratch. The initial goal was just to render a simple 3D scene in the browser at a reasonable frame rate. It evolved into a small renderer that can: • Run locally or on the web using wgpu and WebAssembly • Perform mesh rendering with a Bounding Volume Hierarchy (BVH) for acceleration • Simulate both direct and indirect illumination for photorealistic results • Be…
Nov 2025 · github.com
- 5IM
2023 · vram.asmirnov.xyz
- 6SS
Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai
- 7RT
2023 · antimatter15.com
- 8SA
2024 · shadeup.dev
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- 10SL
Apr 2026 · eng.basement.studio
- 11G2
Back in the old days, people used to do general-purpose GPU programming by using shaders like GLSL. This is what inspired NVIDIA (and other companies) to eventually create CUDA (and friends). This is an implementation of GPT-2 using WebGL and shaders. Enjoy!
2025 · github.com
- 12UA
The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com
- 13IR
Jun 2026 · github.com
- 14IV
This is a GPU "software" raytracer (i.e. using manual ray-scene intersections and not RTX) written using the WebGPU API that renders glTF scenes. It supports many materials, textures, material & normal mapping, and heavily relies on multiple importance sampling to speed up convergence.
2024 · github.com
- 151T
2020 · youtube.com
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Hi HN, I built PantheonGPU because I wanted a better way to answer a simple question: is this GPU actually healthy and performing the way it should? A GPU can show normal temperatures and utilization and still be underperforming, unstable under certain workloads, or have memory, PCIe, or configuration issues. PantheonGPU actively tests the GPU instead of only monitoring telemetry. It currently includes 45+ tests covering compute, tensor workloads, memory, cache, PCIe, thermals, stability, and AI/LLM inference. It supports both NVIDIA CUDA and AMD ROCm. I’m also exploring a larger use…
19d ago · pantheongpu.com
- 17VR
I've been going through Cem Yuksel's "Introduction to Computer Graphics" course and thought that writing a volume renderer would be a good way to test my knowledge. It is a common technique used to render 3D medical data. Works by ray marching a specific step size, reading a 3D texture (e.g. MRI data), and calculating opacity values. Code should be easy to get started with for anyone familiar with the JS ecosystem. Questions for the HN community: I spent 20-25% of the entire time just setting up the project and fighting issues with the JavaScript ecosystem. This experience has made me…
2024 · github.com
- 18BA
Benchi is a CLI tool for running benchmarks and collecting metrics. It's using Docker Compose to orchestrate the infrastructure and tools being benchmarked, making it repeatable and runnable on different machines. It allows you to run the same benchmark for different tools and compare the collected results. The repository contains a simple example. For a more elaborate example see how we use Benchi to compare data pipelines running on Conduit and Kafka Connect, two data streaming tools (still work in progress): https://github.com/ConduitIO/streaming-benchmarks
2025 · github.com
- 19WH
2022 · memgraph.com
- 20WP
This is a small particles simulation that can run either with WebGPU (GPU Compute) or with the CPU, and it can be changed in real time
2023 · github.com
- 21PS
2019 · github.com
- 22LF
100% bootstrapped new startup. It lets you fine tune Mistral-7B and SDXL. In particular, for the LLM fine tuning we implemented a dataprep pipeline that turns websites/pdfs/doc files into question-answer pairs for training the small LLM using an big LLM. It includes a GPU scheduler that can do finegrained GPU memory scheduling (Kubernetes can only do whole-GPU, we do it per-GB of GPU memory to pack both inference and fine tuning jobs into the same fleet) to fit model instances into GPU memory to optimally trade off user facing latency with GPU memory utilization It's a pretty…
2023 · docs.helix.ml
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