Demo Data from EDBT 2026 / reviewers in the wild / expert
Zhesheng Shen
dblp:270/3944
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 75% GPUs and heterogeneous computing · 25% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › simulation › architectural simulation
GPU architecture simulation |
0.4 | 1 | 2020 | Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling · ISCA 2020 |
GPUs and heterogeneous computing
GPU microarchitecture |
0.4 | 1 | 2020 | Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling · ISCA 2020 |
Performance modeling and evaluation › processor performance modeling › accelerator performance modeling
GPU performance modeling |
0.4 | 1 | 2020 | Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling · ISCA 2020 |
Performance modeling and evaluation
simulation |
0.4 | 1 | 2020 | Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling · ISCA 2020 |
Methods — techniques the papers use, named apart from their topics
trace-driven simulation · 0.4microbenchmark validation · 0.4execution-driven simulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Accel-Sim: An Extensible Simulation Framework for Validated GPU ModelingabstractIn computer architecture, significant innovation frequently comes from industry. However, the simulation tools used by industry are often not released for open use, and even when they are, the exact details of industrial designs are not disclosed. As a result, research in the architecture space must ensure that assumptions about contemporary processor design remain true.To help bridge the gap between opaque industrial innovation and public research, we introduce three mechanisms that make it much easier for GPU simulators to keep up with industry. First, we introduce a new GPU simulator frontend that minimizes the effort required to simulate different machine ISAs through trace-driven simulation of NVIDIA's native machine ISA, while still supporting execution-driven simulation of the virtual ISA. Second, we extensively update GPGPU-Sim's performance model to increase its level of detail, configurability and accuracy. Finally, surrounding the new frontend and flexible performance model is an infrastructure that enables quick, detailed validation. A comprehensive set of microbenchmarks and automated correlation plotting ease the modeling process.We use these three new mechanisms to build Accel-Sim, a detailed simulation framework that decreases cycle error 79 percentage points, over a wide range of 80 workloads, consisting of 1,945 kernel instances. We further demonstrate that Accel-Sim is able to simulate benchmark suites that no other open-source simulator can. In particular, we use Accel-sim to simulate an additional 60 workloads, comprised of 11,440 kernel instances, from the machine learning benchmark suite Deepbench. Deepbench makes use of closed-source, hand-tuned kernels with no virtual ISA implementation. Using a rigorous counter-by-counter analysis, we validate Accel-Sim against contemporary GPUs.Finally, to highlight the effects of falling behind industry, this paper presents two case-studies that demonstrate how incorrect baseline assumptions can hide new areas of opportunity and lead to potentially incorrect design decisions. Mahmoud Khairy, Zhesheng Shen, Tor M. Aamodt, Timothy G. Rogers |
ISCA | 2 |