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The ANTAREX Approach to Autotuning and Adaptivity for Energy Efficient HPC Systems

Cristina Silvano, Giovanni Agosta, Stefano Cherubin, Davide Gadioli, Gianluca Palermo, Andrea Bartolini, Luca Benini, Jan Martinovic, Martin Palkovic, Katerina Slaninova, Joao Bispo, Joao M. P. Cardoso, Rui Abreu, Pedro Pinto, Carlo Cavazzoni, Nico Sanna, Andrea R. Beccari, Radim Cmar, Erven Rohou

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Tags: Compilers, Computer science, DSL, Energy-efficient computing, OpenCL

August 1, 2016 by hgpu

Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer

Alina Sirbu, Ozalp Babaoglu

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Package, Python, Task scheduling

January 26, 2016 by hgpu

Climbing Mont Blanc – A Training Site for Energy Efficient Programming on Heterogeneous Multicore Processors

Lasse Natvig, Torbjorn Follan, Simen Stoa, Sindre Magnussen, Antonio Garcia Guirado

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Tags: Computer science, Energy-efficient computing, Heterogeneous systems, OpenCL, OpenMP, Pthreads

November 11, 2015 by hgpu

A Survey Of Architectural Techniques for Near-Threshold Computing

Sparsh Mittal

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Tags: cpu, Energy-efficient computing, low voltage computing, Memory, Power-efficient computing, survey

September 7, 2015 by sparsh0mittal

MemcachedGPU: Scaling-up Scale-out Key-value Stores

Tayler H. Hetherington, Mike O'Connor, Tor M. Aamodt

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Tags: Computer science, CUDA, Databases, Energy-efficient computing, nVidia, nVidia GeForce GTX 750 Ti, Package, Tesla K20, Tesla K40

August 27, 2015 by hgpu

Towards Modeling Energy Consumption of Xeon Phi

Gary Lawson, Masha Sosonkina, Yuzhong Shen

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Molecular dynamics

May 28, 2015 by hgpu

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Cluster computing, Computer science, CUDA, Distributed computing, Energy-efficient computing, GPU cluster, nVidia, Tesla K20

March 25, 2015 by hgpu

GPGPU Performance and Power Estimation Using Machine Learning

Gene Wu, Joseph L. Greathouse, Alexander Lyashevsky, Nuwan Jayasena, Derek Chiou

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Tags: ATI, ATI Radeon HD 7970, Computer science, Energy-efficient computing, Machine learning, Neural networks, OpenCL

March 12, 2015 by hgpu

Energy-and cost-efficient Lattice-QCD computations using graphics processing units

Matthias Bach

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Tags: Algorithms, AMD FirePro S10000, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Energy-efficient computing, High Energy Physics - Lattice, OpenCL, Physics, QCD, Thesis

March 3, 2015 by hgpu

A Survey of Architectural Techniques For DRAM Power Management

Sparsh Mittal

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Tags: Architecture, DVFS, Energy-efficient computing, HPC, main memory, Power-efficient computing

February 9, 2015 by sparsh0mittal

Power Management Techniques for Data Centers: A Survey

Sparsh Mittal

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Tags: Architecture, big data, cpu, Energy-efficient computing, HPC, Power-efficient computing

February 8, 2015 by sparsh0mittal

A Survey of Power Management Techniques for Phase Change Memory

Sparsh Mittal

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Tags: cpu, Energy-efficient computing, GPU, Memory, non-volatile memory, Power-efficient computing

February 3, 2015 by sparsh0mittal

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

microSYCL: SYCL micro-benchmarks repository

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

XaaS containers

Acceleration as a Service (XaaS) Source Containers

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?

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