most citedCharacterizing GPU Energy Usage in Exascale-Ready Portable Science Applications

3 citations · 6 across the 9 of their papers we have counts for

collaborators

11 papers

cs.LG2026

Product-Aware Deterministic Rounding for Quantized Matrix Multiplication

Piyush Sao, Narasinga Miniskar, Pedro Valero-Lara +2

Scalar rounding decisions interact through matrix multiplication. We study deterministic product-aware rounding after scales, clipping bounds, and grids are fixed, with each active…

cs.IT2026

A Nuclear-Norm Lower Bound for Dithered Scalar Quantization of Matrix Products

Piyush Sao, Narasinga Miniskar, Pedro Valero-Lara +2

We consider the problem of minimizing error in quantized matrix multiplication . Scalar quantization of the factors introduces rounding errors whose scale depends on the maxi…

cs.PL2026

JLIR: A Julia-Native MLIR-Inspired Intermediate Representation with Automatic JACC Kernel Extraction

Narasinga Rao Miniskar, Seyong Lee, Keita Teranishi +1

The Multi-Level Intermediate Representation (MLIR) has made reusable compiler infrastructure practical for domain-specific computation. However, MLIR's strong compile-time type req…

math.NA2026

A Second-Moment Theory for Floating-Point Reduction Trees

Piyush Sao, Narasinga Miniskar, Pedro Valero-Lara +2

Summation error depends on partial-sum order, which standard worst-case bounds omit. To capture this dependence, we derive an exact mean-square error (MSE) recurrence for a binary…

cs.LG2026

Contraction-Gauge Preconditioning for Quantized Matrix Multiplication

Piyush Sao, Narasinga Miniskar, Pedro Valero-Lara +2

We study low-precision computation of C=AB with both factors quantized. We derive an exact finite-dimensional identity for the expected squared product error under independent, zer…

quant-ph2026

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

Narasinga Rao Miniskar, Elaine Wong, Vicente Leyton-Ortega +2

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical…

quant-ph2026

LightStim: A Framework for QEC Protocol Evaluation and Prototyping with Automated DEM Construction

Xiang Fang, Ming Wang, Yue Wu +6

Fault-tolerant quantum computing increasingly demands rigorous, circuit-level evaluation of diverse quantum error correction (QEC) protocols and efficient prototyping of new ones.…

quant-ph2025★ 1 cited

Q-IRIS: The Evolution of the IRIS Task-Based Runtime to Enable Classical-Quantum Workflows

Narasinga Rao Miniskar, Mohammad Alaul Haque Monil, Elaine Wong +4

Extreme heterogeneity in emerging HPC systems are starting to include quantum accelerators, motivating runtimes that can coordinate between classical and quantum workloads. We pres…

cs.SE2025★ 2 cited

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

Keita Teranishi, Harshitha Menon, William F. Godoy +25

We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular…

cs.PF2025★ 3 cited

Characterizing GPU Energy Usage in Exascale-Ready Portable Science Applications

William F. Godoy, Oscar Hernandez, Paul R. C. Kent +8

We characterize the GPU energy usage of two widely adopted exascale-ready applications representing two classes of particle and mesh solvers: (i) QMCPACK, a quantum Monte Carlo pac…

cs.ET2025

Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming

Devin Pohl, Aaron Young, Kazi Asifuzzaman +2

Advances in novel hardware devices and architectures allow Spiking Neural Network evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network s…