⚡ CUDA - saeedesmaili

Less-relevant results

CommBench: Can LLMs Write Correct and Efficient GPU Communication Code?

🧠LLMs

uccl-project.github.io··Hacker News

AgentCompile: An LLM-Guided Compiler for Direct CUDA Inference

🔬Deep Learning Academic

arxiv.org·

Modern GPU Programming in Rust (2024) [video]

🔬Deep Learning Video

youtube.com··Hacker News

DeepSeekV4 1.6T Day 0 to Day 43 Performance Over Time - Huawei, GB300 NVL72, MI355X, B200

🧠LLM Inference News

newsletter.semianalysis.com

··Hacker News

Profiling in PyTorch (Part 2): From Nn.Linear to a Fused MLP

🤖Machine Learning Blog

huggingface.co··Hacker News

1-bit and 1.58 bit LLM Benchmarking on Jetson Orin Nano Super | Bonsai LM

🤖Data science

smolhub.com··r/LocalLLaMA

Huawei-led team claims it post-trained DeepSeek's 1.6-trillion-parameter model — 1,000 Ascend 910C chips used in training

🔬Deep Learning News

tomshardware.com

··Hacker News

AmrDeveloper/Turtle: A Heterogeneous Pythonic 🐍 language to practice targeting CPU & GPU in the same program on Mobile Devices Influenced by Python, Mojo and CUDA

🔬Deep Learning Code

github.com··Hacker News

AutoMegaKernel: A Statically-Checked Agent Harness for Self-Retargeting Megakernel Synthesis

🔬Deep Learning Academic

arxiv.org··Hacker News

Orchestrate your LLM pipeline. Locally

🎯Fine-tuning

llmforge.app··Hacker News

Two Leaps to 1000 Tokens/s on a 1T-Parameter Model: On Inference Systems, Execution Boundaries, and Co-Design

🧠LLM Inference Blog

tilert.ai··Hacker News

Release TorchCodec 0.14: HDR Video Decoding for CPU & CUDA, and Fast Wav Decoder · meta-pytorch/torchcodec

🔬Deep Learning Code

github.com··Hacker News

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

🔬Deep Learning Academic

arxiv.org·

Introducing Piper: A Programmable Distributed Training System

🔥PyTorch Academic Blog

syfi.cs.washington.edu··Hacker News

Unpacking AI: The Hardware Behind AI

🔬Deep Learning News

pathtostaff.com··Hacker News

Characterizing Software Aging in GPU-Based LLM Serving Systems

🧠LLM Inference Academic

arxiv.org·

Nvidia DGX Spark GB10 – AI Models and Guide with vLLM and Autonomous Script

🧠LLM Inference Code

github.com··Hacker News

Gram Newton-Schulz: A Fast, Hardware-Aware Newton-Schulz Algorithm for Muon

📈Optimization Blog

tridao.me··Hacker News

Exploiting GPU Tensor Cores from Java using Babylon [Juan Fumero]

KJLdefeated/RL.cu: RLVR training for LLM in CUDA/C++

CommBench: Can LLMs Write Correct and Efficient GPU Communication Code?

AgentCompile: An LLM-Guided Compiler for Direct CUDA Inference

Modern GPU Programming in Rust (2024) [video]

DeepSeekV4 1.6T Day 0 to Day 43 Performance Over Time - Huawei, GB300 NVL72, MI355X, B200

Profiling in PyTorch (Part 2): From Nn.Linear to a Fused MLP

1-bit and 1.58 bit LLM Benchmarking on Jetson Orin Nano Super | Bonsai LM

Huawei-led team claims it post-trained DeepSeek's 1.6-trillion-parameter model — 1,000 Ascend 910C chips used in training

AmrDeveloper/Turtle: A Heterogeneous Pythonic 🐍 language to practice targeting CPU & GPU in the same program on Mobile Devices Influenced by Python, Mojo and CUDA

AutoMegaKernel: A Statically-Checked Agent Harness for Self-Retargeting Megakernel Synthesis

Orchestrate your LLM pipeline. Locally

Two Leaps to 1000 Tokens/s on a 1T-Parameter Model: On Inference Systems, Execution Boundaries, and Co-Design

Release TorchCodec 0.14: HDR Video Decoding for CPU & CUDA, and Fast Wav Decoder · meta-pytorch/torchcodec

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

Introducing Piper: A Programmable Distributed Training System

Unpacking AI: The Hardware Behind AI

Characterizing Software Aging in GPU-Based LLM Serving Systems

Nvidia DGX Spark GB10 – AI Models and Guide with vLLM and Autonomous Script

Gram Newton-Schulz: A Fast, Hardware-Aware Newton-Schulz Algorithm for Muon