Electrical & Computer Engineering

eScholarship stats: History by Item for June through September, 2026

Item	Title	Total requests	2026-09	2026-08	2026-07	2026-06
1sm051d2	Dynamic Mesh Processing on the GPU	869	103	209	237	320
0x86w4w1	Optimized GPU Implementation of Grid Refinement in Lattice Boltzmann Method	429	85	110	99	135
8r5848vp	RXMesh: A GPU Mesh Data Structure	344	82	106	64	92
6kp4p18t	Graph Coloring on the GPU	336	151	115	32	38
3v12f7dn	Quotient Filters: Approximate Membership Queries on the GPU	249	31	77	44	97
9fz7k633	Neon: A Multi-GPU Programming Model for Grid-based Computations	228	44	45	80	59
48j4k7np	Dynamic Graphs on the GPU	197	43	73	37	44
9v75738g	Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs	166	31	58	33	44
5qd0r4ws	Parallel Algorithms and Dynamic Data Structures on the Graphics Processing Unit: a warp-centric approach	161	44	61	24	32
37j8j27d	High-Performance Linear Algebra-based Graph Framework on the GPU	160	34	69	24	33
7j96s061	Maximum Clique Enumeration on the GPU	157	38	43	31	45
2p48q0zg	A Dynamic Hash Table for the GPU	154	44	33	42	35
6rt535s6	Building a Performance Model for Deep Learning Recommendation Model Training on GPUs	148	29	37	25	57
7dc8d5vb	Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset	136	23	36	27	50
4sk284kw	Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection	135	29	45	24	37
8413c9hb	Extension of the Hot-Switching Reliability of RF-MEMS Switches Using A Series ContactProtection Technique	123	19	46	22	36
5mv1s1gg	Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms	121	17	30	22	52
9bd842z6	Scalable Breadth-First Search on a GPU Cluster	118	42	32	21	23
65t741zg	GPU LSM: A Dynamic Dictionary Data Structure for the GPU	108	19	28	25	36
9vm907zv	High Efficiency Micromachined Sub-THz Channels for Low Cost Interconnect for Planar Integrated Circuits	75	13	27	9	26

Top

Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.