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Rajesh Shashi Kumar

dblp:392/3149 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0009-4743-9452ORCID · reported

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 · 77% Interconnection networks and networks-on-chip · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
GPUs and heterogeneous computing › GPU architecture
multi-chip module GPU
0.812024
CPElide: Efficient Multi-Chiplet GPU Implicit Synchronization · MICRO 2024
Interconnection networks and networks-on-chip
die-to-die interconnect
0.212024
CPElide: Efficient Multi-Chiplet GPU Implicit Synchronization · MICRO 2024
YearPublicationVenuePosition
2024 CPElide: Efficient Multi-Chiplet GPU Implicit Synchronization
abstract
Chiplets are transforming computer system designs, allowing system designers to combine heterogeneous computing resources at unprecedented scales. Breaking larger, mono-lithic chips into smaller, connected chip lets helps performance continue scaling, avoids die size limitations, improves yield, and reduces design and integration costs. However, chip let-based designs introduce an additional level of hierarchy, which causes indirection and non-uniformity. This clashes with typ-ical heterogeneous systems: unlike CPU-based multi-chiplet systems, heterogeneous systems do not have significant OS support or complex coherence protocols to mitigate the impact of this indirection. Thus, exploiting locality across application phases is harder in multi-chiplet heterogeneous systems. We propose CPElide, which utilizes information already avail-able in heterogeneous systems' embedded microprocessor (the command processor) to track inter-chiplet data dependencies and aggressively perform implicit synchronization only when necessary, instead of conservatively like the state-of-the-art HMG. Across 24 workloads CPElide improves average performance (13%, 19%), energy (14%, 11 %), and network traffic (14%,17%), respectively, over current approaches and HMG.
Preyesh Dalmia, Rajesh Shashi Kumar, Matthew D. Sinclair
MICRO2