Cover Image

TrioSeq: A Novel Approach to Accelerate Triplet Sequence Alignment on GPUs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Graça, Miguel, Ilic, Aleksandar
Format:	Preprint
Published:	2026
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PRISM: Processing-In-Memory Sparse MTTKRP for Tensor Decomposition Acceleration
by: Pacheco, Daniel, et al.
Published: (2026)

CARM Tool: Cache-Aware Roofline Model Automatic Benchmarking and Application Analysis
by: Morgado, José, et al.
Published: (2026)

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with SW Sequence Alignment
by: Costanzo, Manuel, et al.
Published: (2024)

Accelerating Maximal Biclique Enumeration on GPUs
by: Hsieh, Chou-Ying, et al.
Published: (2024)

Accelerating Sparse Matrix-Matrix Multiplication on GPUs with Processing Near HBMs
by: Li, Shiju, et al.
Published: (2025)

AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping
by: Park, Seongyeon, et al.
Published: (2024)

AMPED: Accelerating MTTKRP for Billion-Scale Sparse Tensor Decomposition on Multiple GPUs
by: Wijeratne, Sasindu, et al.
Published: (2025)

Popcorn: Accelerating Kernel K-means on GPUs through Sparse Linear Algebra
by: Bellavita, Julian, et al.
Published: (2025)

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs
by: Ho, Andrew, et al.
Published: (2024)

Cuckoo-GPU: Accelerating Cuckoo Filters on Modern GPUs
by: Dortmann, Tim, et al.
Published: (2026)

Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training
by: Sun, Ao, et al.
Published: (2024)

Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
by: He, Guoliang, et al.
Published: (2025)

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software
by: Samsi, Siddharth, et al.
Published: (2025)

RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
by: Xie, Xi, et al.
Published: (2024)

An Adaptive Distributed Stencil Abstraction for GPUs
by: Bhosale, Aditya, et al.
Published: (2025)

Parallelizing Maximal Clique Enumeration on GPUs
by: Almasri, Mohammad, et al.
Published: (2022)

Optimizing sDTW for AMD GPUs
by: Latta-Lin, Daniel, et al.
Published: (2024)

Run-time application migration using checkpoint/restore in userspace
by: Tošić, Aleksandar
Published: (2023)

HetCCL: Accelerating LLM Training with Heterogeneous GPUs
by: Kim, Heehoon, et al.
Published: (2026)

Serving Compound Inference Systems on Datacenter GPUs
by: Devata, Sriram, et al.
Published: (2026)

Fast Kronecker Matrix-Matrix Multiplication on GPUs
by: Jangda, Abhinav, et al.
Published: (2024)

Optimal Workload Placement on Multi-Instance GPUs
by: Turkkan, Bekir, et al.
Published: (2024)

Parallel DNA Sequence Alignment on High-Performance Systems with CUDA and MPI
by: Zwaka, Linus
Published: (2024)

Straggler Tolerant and Resilient DL Training on Homogeneous GPUs
by: Zhang, Zeyu, et al.
Published: (2025)

RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs
by: Brock, Benjamin, et al.
Published: (2023)

Accurate Computation of the Logarithm of Modified Bessel Functions on GPUs
by: Plesner, Andreas, et al.
Published: (2024)

Accelerating MoE with Dynamic In-Switch Computing on Multi-GPUs
by: Zhang, Qijun, et al.
Published: (2026)

AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs
by: Akinwande, Victor, et al.
Published: (2024)

Managing Multi Instance GPUs for High Throughput and Energy Savings
by: Saraha, Abhijeet, et al.
Published: (2025)

Analytical Performance Estimation during Code Generation on Modern GPUs
by: Ernst, Dominik, et al.
Published: (2022)

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
by: Jiang, Youhe, et al.
Published: (2025)

HexiSeq: Accommodating Long Context Training of LLMs over Heterogeneous Hardware
by: Liang, Yan, et al.
Published: (2026)

Hive Hash Table: A Warp-Cooperative, Dynamically Resizable Hash Table for GPUs
by: Polak, Md Sabbir Hossain, et al.
Published: (2025)

Scaling to 32 GPUs on a Novel Composable System Architecture
by: Ihnotic, John
Published: (2024)

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL
by: Gao, Wei, et al.
Published: (2026)

Anonymized Network Sensing using C++26 std::execution on GPUs
by: Mandulak, Michael, et al.
Published: (2025)

Ocularone-Bench: Benchmarking DNN Models on GPUs to Assist the Visually Impaired
by: Raj, Suman, et al.
Published: (2025)

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs
by: Ekelund, Jonah, et al.
Published: (2025)

FlashSketch: Sketch-Kernel Co-Design for Fast Sparse Sketching on GPUs
by: Dwaraknath, Rajat Vadiraj, et al.
Published: (2026)

FREESH: Fair, Resource- and Energy-Efficient Scheduling for LLM Serving on Heterogeneous GPUs
by: He, Xuan, et al.
Published: (2025)