Doru Thom Popovici

Doru Thom Popovici
Lawrence Berkeley National Laboratory | LBL · Computational Research Division (CRD)

Doctor of Philosophy

About

20
Publications
1,428
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177
Citations
Citations since 2016
15 Research Items
175 Citations
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Introduction
Skills and Expertise

Publications

Publications (20)
Chapter
Small prime-sized discrete Fourier transforms appear in various applications from quantum mechanics, material sciences and machine learning. The typical implementation of the discrete Fourier transform for such problem sizes is done as a cyclic convolution using algorithms like Rader or Bluestein. However, these approaches exhibit extra computation...
Preprint
We present the design of a solver for the efficient and high-throughput computation of the marginalized graph kernel on General Purpose GPUs. The graph kernel is computed using conjugate gradient to solve a generalized Laplacian of the tensor product between a pair of graphs. To cope with the large gap between the instruction throughput and the mem...
Preprint
Full-text available
Multi-dimensional discrete Fourier transforms (DFT) are typically decomposed into multiple 1D transforms. Hence, parallel implementations of any multi-dimensional DFT focus on parallelizing within or across the 1D DFT. Existing DFT packages exploit the inherent parallelism across the 1D DFTs and offer rigid frameworks, that cannot be extended to in...
Article
Full-text available
In this paper, we address the question of how to automatically map computational kernels to highly efficient code for a wide range of computing platforms and establish the correctness of the synthesized code. More specifically, we focus on two fundamental problems that software developers are faced with: performance portability across the ever-chan...
Conference Paper
Full-text available
Achieving high performance for compute bounded numerical kernels typically requires an expert to hand select an appropriate set of Single-instruction multiple-data (SIMD) instructions, then statically scheduling them in order to hide their latency while avoiding register spilling in the process. Unfortunately, this level of control over the code fo...
Conference Paper
Upsampling of a multi-dimensional data-set is an operation with wide application in image processing and quantum mechanical calculations using density functional theory. For small up sampling factors as seen in the quantum chemistry code ONETEP, a time-shift based implementation that shifts samples by a fraction of the original grid spacing to fill...
Article
Full-text available
Real-time system level implementations of complex Synthetic Aperture Radar (SAR) image reconstruction algorithms have always been challenging due to their data intensive characteristics. In this paper, we propose a basis vector transform based novel algorithm to alleviate the data intensity and a 3D-stacked logic in memory based hardware accelerato...
Data
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Conference Paper
Full-text available
Formal behavioral models of software services are used as input by analysis tools which check their properties on hand of the given models. However, there is a gap between the real systems which have to be validated and their abstract models. This work proposes to bridge this gap by tools which extract behavioral models from software services imple...
Conference Paper
Full-text available
Many techniques used for discovering faults and vulnerabilities in distributed systems and services require as inputs formal behavioral models of the systems under validation. Such models are traditionally written by hand, according to the specifications which are known, leading to a gap between the real systems which have to be validated and their...

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