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Graphics Processing Unit (GPU)

Definition
AI-generated

A Graphics Processing Unit (GPU) is a many-core processor optimized for parallel numeric operations, especially matrix and tensor computations used in deep learning and large-scale scientific workloads.

Topics
Compute and Hardware Machine learning concepts
Synonyms
GPU
Plural
GPUs
Related
CPU Compute Unified Device Architecture (CUDA) Compute Cluster

Why it matters in GWAS

GPU acceleration can substantially reduce runtime for selected genomics and ML-heavy tasks, including model training, embedding workflows, and some simulation or inference pipelines used in post-GWAS analyses.

Example usage

"Fine-mapping model training was moved to GPUs to reduce runtime from days to hours."

CPU Compute Unified Device Architecture (CUDA) Compute Cluster High-Performance Computing (HPC) Slurm Machine Learning (ML) Deep Learning
Related-term network

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Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • NVIDIA. GPU Computing Basics. https://developer.nvidia.com/gpu-computing
← Genome Aggregation Database (gnomAD) Gradient Descent →

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