activity
20242026
most citedSUperman: Efficient Permanent Computation on GPUs

2 citations · 3 across the 10 of their papers we have counts for

collaborators

10 papers

cs.DS2026

The Quick and the Dead: Estimating Sparse-Matrix Permanents with Adaptive Work Filtering

Deniz Elbek, Yiğit Manafi, Zeynep Gürdal +2

Rasmussen's permanent estimator is a simple and unbiased estimator for the permanent of a binary matrix, but its practical performance can be limited by trajectories that terminate…

quant-ph2026

Graph-Aware Exact Branch-and-Bound with Device Profiles for Static Qubit Allocation

Kamer Kaya

Static qubit allocation maps a circuit's logical qubits to a sparse physical device while minimising an interaction-weighted physical-distance cost function, yielding a rectangular…

cs.DC2026

Graph Traversal on Tensor Cores: A BFS Framework for Modern GPUs

Deniz Elbek, Kamer Kaya

Modern GPUs have Tensor Cores (TCs) capable of extremely high-throughput matrix operations, yet graph algorithms remain difficult to accelerate because of their irregular and data-…

cs.CR2026

Diagonal Packing for Efficient Homomorphic Sparse Matrix-Vector Multiplication

Kemal Mutluergil, Deniz Elbek, Kamer Kaya +1

Homomorphic encryption (HE) enables computation over encrypted data but incurs a substantial overhead. For sparse matrix-vector multiplication, the widely used Halevi-Shoup scheme…

cs.DC2025

BLEST: Blazingly Efficient BFS using Tensor Cores

Deniz Elbek, Kamer Kaya

Breadth-First Search (BFS) is a fundamental graph kernel that underpins a wide range of applications. While modern GPUs provide specialised Matrix-Multiply-Accumulate (MMA) units,…

cs.DC2025★ 2 cited

SUperman: Efficient Permanent Computation on GPUs

Deniz Elbek, Fatih Taşyaran, Bora Uçar +1

The permanent is a function, defined for a square matrix, with applications in various domains including quantum computing, statistical physics, complexity theory, combinatorics, a…

cs.DC2025

Fully-Automated Code Generation for Efficient Computation of Sparse Matrix Permanents on GPUs

Deniz Elbek, Kamer Kaya

Registers are the fastest memory components within the GPU's complex memory hierarchy, accessed by names rather than addresses. They are managed entirely by the compiler through a…

cs.IR2024★ 1 cited

A Retrieval-Augmented Generation Framework for Academic Literature Navigation in Data Science

Ahmet Yasin Aytar, Kemal Kilic, Kamer Kaya

In the rapidly evolving field of data science, efficiently navigating the expansive body of academic literature is crucial for informed decision-making and innovation. This paper p…

cs.DC2024

DiFuseR: A Distributed Sketch-based Influence Maximization Algorithm for GPUs

Gökhan Göktürk, Kamer Kaya

Influence Maximization (IM) aims to find a given number of "seed" vertices that can effectively maximize the expected spread under a given diffusion model. Due to the NP-Hardness o…

cs.SI2024

Accelerating Spanning-Centrality Approximation with Sampling-Aware Vectorized Random Walks

Gökhan Göktürk, Kamer Kaya

Spanning centrality quantifies an edge's importance through its share of a graph's spanning trees, and approximating it for all edges (AESC) requires processing large volumes of ir…