EDBT 2026 Demo / reviewers in the wild / expert
Rishkul Kulkami
dblp:320/8147
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021
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 |
GPUs and heterogeneous computing · 60% Processor architecture and microarchitecture · 40% | |
| Computer graphics and multimedia
1 paper |
Rendering · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
GPUs and heterogeneous computing
control flow divergence |
0.6 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
GPUs and heterogeneous computing
GPU microarchitecture |
0.6 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
Processor architecture and microarchitecture
latency hiding |
0.6 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
Processor architecture and microarchitecture › pipelining
pipeline stall |
0.6 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
GPUs and heterogeneous computing › GPU scheduling
warp scheduling |
0.6 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
Rendering
ray tracing |
0.2 | 1 | 2022 | GPU Subwarp Interleaving · HPCA 2022 |
Methods — techniques the papers use, named apart from their topics
simulation · 1.1microbenchmarking · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | GPU Subwarp InterleavingabstractRaytracing applications have naturally high thread divergence, low warp occupancy and are limited by memory latency. In this paper, we present an architectural enhancement called Subwarp Interleaving that exploits thread divergence to hide pipeline stalls in divergent sections of low warp occupancy workloads. Subwarp Interleaving allows for fine-grained interleaved execution of diverged paths within a warp with the goal of increasing hardware utilization and reducing warp latency. However, notwithstanding the promise shown by early microbenchmark studies and an average performance upside of 6.3% (up to 20%) on a simulator across a suite of raytradng application traces, the Subwarp Interleaving design feature has shortcomings that preclude its near-term implementation. This paper introduces the reader to the challenges of raytradng and discusses a novel micro-architectural approach that, on paper, addresses many of the challenges. A thorough analysis of the idea on a production simulator reveals that the high-level motivating statistics are optimistic, and second-order effects, along with other architectural sharp edges, limit the idea’s potential. We identify Subwarp Interleaving’s primary limiters for an NVIDIA Tbring-like architecture, and we outline the conditions under which the approach could be more effective. Sana Damani, Mark Stephenson, Ram Rangan, Daniel R. Johnson, Rishkul Kulkami, Stephen W. Keckler |
HPCA | 5 |