Re:A primer on GPUs and kernel optimization
by nomi_uw on Tuesday November 10, 2026 @10:03PM
(#50449310)
Seems like the kernel portion of that competition is closed. I can probably compare whatever the serving winner is against JamInfer when it's out (seems like they start that track on the 12th). The top of the article shows the e2e times on some math RL tasks, with fp8 weights/activations/KV, comparing against SGLang on two models. They use the same concurrent batch size, quantization scheme, and the final lengths were about the same.
30B-A3B MoE
Jam - 67,241
SGLang - 44,696
+50.4%
8B Dense
Jam - 58,821
SGLang - 41,759
+40.9%
Math RL is pure decode, so kernels are the most major factor here.
Re:A primer on GPUs and kernel optimization
by augment_me on Tuesday November 10, 2026 @11:43PM
(#50449826)
Oh sorry I didn't know it closed. I understand, I was mostly curious because I hear this every now and then, people seemingly not running into the issues of reward-hacking with agentic harnesses which contradicts a lot of findings from people and myself in these competitions.
Re:A primer on GPUs and kernel optimization
by nomi_uw on Tuesday November 10, 2026 @11:59PM
(#50449903)
I don't think it's not a problem, and I'm sure it pops up extremely often in the case of competitions when things are won by margins of +0.01x and hundreds of people are chipping at it with agents for days. This is a very different scenario to what I assume most people might be doing, though.
Thanks for bringing up these points, it's definitely good food for thought to add to the blog!
Look at this challenge:
https://openkernelchallenge.dev/#leaderboard
If you have the tokens, let your harness go at let's say the first bf16 problem, I am curious how far you will get with it (1.73x is the leader and 2.04x is roofline). I think if you manage to get above 1.63x, I would be really interested in learning how you did that.