arXiv AI
FlashSinkhorn 2: Block-Sparse Entropic Optimal Transport
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arXiv Machine Learning
6d ago
Replay the Curvature: Accurate and Scalable NVFP4 Quantization for Large Language Model Inference
arXiv:2609.36654v1 Announce Type: new Abstract: Large language models make weight storage and memory traffic major inference costs, motivating low-precision formats that represent each weight with on...
arXiv Machine Learning
Sep 3
GRADSOLVE: fast exact gradients for ODE ensembles on GPUs
GRADSOLVE is an open‑source JAX library that provides fast, exact reverse‑mode gradients for low‑dimensional ordinary differential equation (ODE) ensembles on NVIDIA GPUs. It records the accepted steps of an adaptive solver and differentiates a fixed‑step replay, yielding the exact discrete adjoint at a lower computational cost than traditional checkpointed methods. Benchmarks show that GRADSOLVE’s forward kernel is 2.8× faster than DiffEqGPU.jl, and its gradient computation is 5.6–14.1× faster than Diffrax’s checkpointed adjoint while maintaining matched forward‑state accuracy across multiple GPU generations.
arXiv AI
Jul 17
A Modern Multimodal Assistant on a 6 GB 2011 GPU: Stage-Validated, All-GPU CUDA Inference for Fermi
arXiv:2607. 14568v1 Announce Type: cross Abstract: A companion study ran a 35B mixture-of-experts model on a 2011 NVIDIA Tesla C2075 (Fermi, sm_20, 6GB) as a GPU-prefill/CPU-decode hybrid, because the 4-bit model did not fit in device memory (arXiv:2606.
arXiv AI
Sep 21
How Much of a Real Workload Can LLM-Generated GPU Kernels Actually Reach?
arXiv:2609.21058v1 Announce Type: cross Abstract: Language models can now write GPU kernels that outperform PyTorch. We evaluate five model configurations on KernelBench level 1 and find that a front...
arXiv AI
Jun 16
FP8 is All You Need (Part 1): Debunking Hardware FP64 as the HPC Holy Grail (June 13th version)
arXiv:2606. 06510v2 Announce Type: replace-cross Abstract: Conventional HPC holds that native hardware FP64 is the irreducible foundation of scientific computing.
arXiv AI
Jun 8
FP8 is All You Need (Part 1): Debunking Hardware FP64 as the HPC Holy Grail
arXiv:2606. 06510v1 Announce Type: cross Abstract: Conventional HPC dogma holds that native hardware FP64 silicon is the irreducible foundation of scientific computing -- the "holy grail" of double-precision simulation.