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PowerNovo2: A generative flow-based approach to non-autoregressive de novo peptide sequencing. [PDF]
PLoS Comput BiolPetrovskiy DV +7 more
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Smart medical system integrating clinical workflows for robust skin cancer detection across heterogeneous pathologies. [PDF]
Sci RepAbugabah A +3 more
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Neurofilament Light Chain from Neuronally Derived Extracellular Vesicles in Differentiating Parkinson's Disease from Essential Tremor with Resting Tremor. [PDF]
Mol NeurobiolMimmi S +11 more
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Investigating the Immune Effects of Radiotherapy in Non-Small Cell Lung Cancer-Results of the PD-RAD Study. [PDF]
Oncol ResCheng S +10 more
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CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications
2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2019GPUs are powerful, massively parallel processors, which require a vast amount of thread parallelism to keep their thousands of execution units busy, and to tolerate latency when accessing its high-throughput memory system. Understanding the behavior of massively threaded GPU programs can be difficult, even though recent GPUs provide an abundance of ...
Lorenz Braun, Holger Fröning
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Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
Recently a GPGPU application had to be redesigned to overcome performance problems. A number of software engineering lessons were learnt from this and other projects. We describe those about obtaining high performance from nVidia GPUs and practical aspects of CUDA C software development.
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Recently a GPGPU application had to be redesigned to overcome performance problems. A number of software engineering lessons were learnt from this and other projects. We describe those about obtaining high performance from nVidia GPUs and practical aspects of CUDA C software development.
openaire +1 more source
IEEE Congress on Evolutionary Computation, 2010
This paper is a report on the migration of the molecular docking application, “Autodock” to NVIDIA CUDA. Autodock is a Drug Discovery Tool that uses a Genetic Algorithm to find the optimal docking position of a ligand to a protein. Speedup of Autodock greatly benefits the drug discovery process.
Sarnath Kannan, Raghavendra Ganji
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This paper is a report on the migration of the molecular docking application, “Autodock” to NVIDIA CUDA. Autodock is a Drug Discovery Tool that uses a Genetic Algorithm to find the optimal docking position of a ligand to a protein. Speedup of Autodock greatly benefits the drug discovery process.
Sarnath Kannan, Raghavendra Ganji
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Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
During six months of intensive nVidia CUDA C programming many bugs were created. We pass on the software engineering lessons learnt, particularly those relevant to parallel general-purpose computation on graphics hardware GPGPU.
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During six months of intensive nVidia CUDA C programming many bugs were created. We pass on the software engineering lessons learnt, particularly those relevant to parallel general-purpose computation on graphics hardware GPGPU.
openaire +1 more source