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GPU accelerated alignment of 3-D CTA with 2-D X-ray data for improved guidance in coronary interventions

C.T. Metz, M. Schaap, S. Klein, A.C. Weustink, N.R. Mollet, C. Schultz, R.J. van Geuns, P.W. Serruys, T. van Walsum, W.J. Niessen

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Tags: Algorithms, Computed radiography, Heart, Image alignment, Image processing, Image registration, Medicine, Rendering

May 20, 2011 by hgpu

GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

G. C. Sharp, N. Kandasamy, H. Singh, M. Folkert

Tags: Brook, Computed radiography, Computer science, Image processing, Medicine, nVidia, nVidia GeForce 8800 GTX

October 28, 2010 by hgpu

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

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