Vulkan `vkpeak` benchmark for the new Arduino Ventuno Q reaches 400+ FP32 GFLOPS.
./vkpeak 0
device = Adreno623
driver = turnip Mesa driver / Mesa 25.2.8-0ubuntu0.24.04.2
fp32-scalar = 417.44 GFLOPS
fp32-vec4 = 438.42 GFLOPS
fp16-scalar = 594.99 GFLOPS
fp16-vec4 = 853.58 GFLOPS
int32-scalar = 109.97 GIOPS
int32-vec4 = 111.09 GIOPS
int16-scalar = 283.50 GIOPS
int16-vec4 = 294.14 GIOPS
int64-scalar = 11.31 GIOPS
int64-vec4 = 6.33 GIOPS
int8-dotprod = 621.29 GIOPS
copy-h2h = 10.11 GBPS
copy-h2d = 11.41 GBPS
copy-d2h = 9.12 GBPS
copy-d2d = 13.66 GBPS
@arduino
Given the TPU buzz, here's a reminder:
"Why systolic architectures?", H.T. Kung, Jan 1982
eecs.harvard.edu/~htk/public…
Kung, H.T. "Why systolic architectures?" Jan 1982:
csis.bits-pilani.ac.in/facul…
Solid `vkpeak` results from the tiny Mali G310 GPU on an Amlogic S905X5M:
𝚏𝚙32-𝚜𝚌𝚊𝚕𝚊𝚛 = 52.58 𝙶𝙵𝙻𝙾𝙿𝚂
𝚏𝚙16-𝚟𝚎𝚌4 = 99.07 𝙶𝙵𝙻𝙾𝙿𝚂
𝚒𝚗𝚝8-𝚍𝚘𝚝𝚙𝚛𝚘𝚍 = 213.88 𝙶𝙸𝙾𝙿𝚂
Gist with `vulkaninfo` output here: gist.github.com/allanmac/5c1…
Good `vkpeak` benchmarks from an RK3588 Arm Mali G610 GPU:
fp32-scalar = 467.89 GFLOPS
fp32-vec4 = 496.97 GFLOPS
fp16-scalar = 471.15 GFLOPS
fp16-vec4 = 978.09 GFLOPS
int8-dotprod = 1884.12 GIOPS
Given $INTC is in the news, it's nice to see that the latest LM Studio and the OpenAI gpt-oss-20b model run at ~47 tok/s on an A770 using Vulkan.
Fun with Google Sheets AI:
=AI("Should I buy this stock? Only answer yes or no.").
Every symbol returns, "I can't provide financial advice" except for NVIDIA and ADOBE where the answer is "No."
I love it!🤷♂️
The terse Section 3.1 of the DeepSeek V3 paper will be interesting to CUDA ninjas.
Hide communications overhead while keeping the 8x GPU node busy:
arxiv.org/pdf/2412.19437
Allan MacKinnon retweeted
Last night I watched an elderly fam member navigate her iPhone for ‘important things and emails’. She is 96 and holding on to be tech relevant. Here is what I observed… 🧵
My dad found this button from his time working on the Lunar Rover.
Apollo 15 was the first to use the moon buggy.
Good ink, it hasn’t faded very much!
You all said “Numerical Linear Algebra, L. Trefethen, and D. Bau. SIAM, (1997)” is invaluable so I got the paperback (PDF out there too).
Allan MacKinnon retweeted
I've been asked about this a lot, so let me provide a quick FAQ.
Q: What's the nature of the issue?
A: Anyone who has bought my book from Amazon in the past few month hasn't bought a genuine copy, but a lower-quality counterfeit copy printed by various fraudulent sellers.
Replying to @fchollet
For instance, if you go to the page of DLwP2 on Amazon, you see that it's being sold by a 3rd party seller named "Sacred Gamez".
If you click "buy", you won't get the actual book from Manning. You get a low-quality counterfeit printed by the fraudulent seller (from the book PDF)
Allan MacKinnon retweeted
A former Wall Street bond trader now coaches the dominant team in competitive high school math. “I used to get paid money,” says Will Frazer. “Now we get trophies.” on.wsj.com/3cgzqBG
My very fast GPU-accelerated radix sort Vulkan library got pulled into the MESA RADV Vulkan driver:
phoronix.com/scan.php?page=n…
#vulkan #gpu #gpucompute #mesa #amd #radeon
Allan MacKinnon retweeted
DietGPU: fast specialized lossless compression on Nvidia GPUs
If you have slow network fabric, this can speedup distributed training by a lot.
Authored by Jeff Johnson (gh:wickedfoo) who wrote a lot of the PyTorch CUDA code and faiss-gpu.
github.com/facebookresearch/…
Allan MacKinnon retweeted
C-for-Metal: High Performance SIMD Programming on Intel GPUs
#OpenCL #CUDA #Package
hgpu.org/?p=24469















