EDBT 2026 Demo / reviewers in the wild / expert
Tomohiro Totoki
dblp:206/3898
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3
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 |
Interconnection networks and networks-on-chip · 91% Parallel and multicore computing · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interconnection networks and networks-on-chip
3d network-on-chip |
0.4 | 1 | 2019 | Sparse 3-D NoCs with Inductive Coupling · DAC 2019 |
Interconnection networks and networks-on-chip
inductive coupling |
0.4 | 1 | 2019 | Sparse 3-D NoCs with Inductive Coupling · DAC 2019 |
Interconnection networks and networks-on-chip
network topology |
0.4 | 1 | 2019 | Sparse 3-D NoCs with Inductive Coupling · DAC 2019 |
Parallel and multicore computing › parallel computing
parallel application performance |
0.1 | 1 | 2019 | Sparse 3-D NoCs with Inductive Coupling · DAC 2019 |
Methods — techniques the papers use, named apart from their topics
randomized network topology generation · 0.4deterministic layout transformation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Sparse 3-D NoCs with Inductive CouplingabstractWireless interconnects based on inductive coupling technology are compelling propositions for designing 3-D integrated chips. This work addresses the heat dissipation problem on such systems. Although effective cooling technologies have been proposed for systems designed based on Through Silicon Via (TSV), their application to systems that use inductive coupling is problematic because of increased wireless-communication distance. For this reason, we propose two methods for designing sparse 3-D chips layouts and Networks on Chip (NoCs) based on inductive coupling. The first method computes an optimized 3-D chip layout and then generates a randomized network topology for this layout. The second method uses a standard stack chip layout with a standard network topology as a starting point, and then deterministically transforms it into either a "staircase" or a "checkerboard" layout. We quantitatively compare the designs produced by these two methods in terms of network and application performance. Our main finding is that the first method produces designs that ultimately lead to higher parallel application performance, as demonstrated for nine OpenMP applications in the NAS Parallel Benchmarks. Michihiro Koibuchi, Lambert T. Leong, Tomohiro Totoki, Naoya Niwa, Hiroki Matsutani, Hideharu Amano, Henri Casanova |
DAC | 3 |
| 2019 | The Case for Water-Immersion Computer BoardsabstractA key concern for a high-power processor is heat dissipation, which limits the power, and thus the operating frequencies, of chips so as not to exceed some temperature threshold. In particular, 3-D chip integration will further increase power density, thus requiring more efficient cooling technology. While air, fluorinert and mineral oil have been traditionally used as coolants, in this study, we propose to directly use tap or natural water due to its superior thermal conductivity. We have developed the "in-water computer" prototypes that rely on a parylene film insulation coating. Our prototypes can support direct water-immersion cooling by taking and draining natural water, while existing cooling requires the secondary coolant (e.g. outside air in cold climates) for cooling the primary coolants that contact chips. Our prototypes successfully reduce by 20 degrees the chip temperature of commodity processor chips. Our analysis results show that the in-water cooling increases the acceptable amount of power density of chips, thus achieving higher operating frequencies of chips. Through a full-system simulation, our results show that the water-immersion chip multiprocessors outperform the counterpart water-pipe cooled and oil-immersion chips by up to 14% and 4.5%, respectively, in terms of execution times of NAS Parallel Benchmarks. Michihiro Koibuchi, Ikki Fujiwara, Naoya Niwa, Tomohiro Totoki, Shoichi Hirasawa |
ICPP | 4 |
| 2017 | A Case for Uni-directional Network Topologies in Large-Scale ClustersabstractDesigning low-latency network topologies of switches is a key objective for next-generation large-scale clusters. Low latency is preconditioned on low hop counts, but existing network topologies have hop counts much larger than theoretical lower bounds. To alleviate this problem, we propose building network topologies based on uni-directional graphs that are known to have hop counts close to theoretical lower bounds. A practical difficulty with uni-directional topologies is switch-by-switch flow control, which we resolve by using hot-potato routing. Cycle-accurate network simulation experiments for various traffic patterns on uni-directional topologies show that hot-potato routing achieves performance comparable to that of conventional deadlock-free routing. Similar experiments are used to compare several uni-directional topologies to bi-directional topologies, showing that the former achieve significantly lower latency and higher throughput. We quantify end-to-end application performance for parallel application benchmarks via discrete-even simulation, showing that uni-directional topologies can lead to large application performance improvements over their bi-directional counterparts. Finally, we discuss practical issues for uni-directional topologies such as cabling complexity and cost, power consumption, and soft-error tolerance. Our results make a compelling case for considering uni-directional topologies for upcoming large-scale clusters. Michihiro Koibuchi, Tomohiro Totoki, Hiroki Matsutani, Hideharu Amano, Fabien Chaix, Ikki Fujiwara, Henri Casanova |
CLUSTER | 2 |