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Development of High-Performance Software Components for Emerging Architectures

Stefan Lemvig Glimberg, Allan Peter Engsig-Karup, Allan S. Nielsen, Bernd Dammann

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Tags: Computer science, CUDA, GPGPU, iterative methods, Mathematics, multigrid, Package, parallel computing, Partial differential equations, Software development

March 12, 2014 by apek

XaaS containers

Acceleration as a Service (XaaS) Source Containers

microSYCL: SYCL micro-benchmarks repository

Exploring SYCL as a Portability Layer for High-Performance Computing on CPUs

SYCL Container

Exploring SYCL for batched kernels with memory allocations

CASS: Cuda-Amd aSSembly

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Cluser of smartphones for edge computing application using TensorFlow

Low-cost edge computing using upcycled smartphones

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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