EDBT 2026 Demo / reviewers in the wild / expert
Vamsi Alla
dblp:383/4205 · also Vamsi Krishna Alla
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0007-3369-2217ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 2 since 2021Software engineering, systems software and programming languages · 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 |
Integrated circuit design · 30% GPUs and heterogeneous computing · 30% High-performance computing · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
GPUs and heterogeneous computing › heterogeneous architecture
accelerated processing unit |
0.8 | 1 | 2024 | Realizing the AMD Exascale Heterogeneous Processor Vision : Industry Product · ISCA 2024 |
High-performance computing › supercomputing
exascale computing |
0.8 | 1 | 2024 | Realizing the AMD Exascale Heterogeneous Processor Vision : Industry Product · ISCA 2024 |
Integrated circuit design
heterogeneous integration |
0.8 | 1 | 2024 | Realizing the AMD Exascale Heterogeneous Processor Vision : Industry Product · ISCA 2024 |
Hardware accelerators and domain-specific architectures
machine learning accelerator |
0.2 | 1 | 2024 | Realizing the AMD Exascale Heterogeneous Processor Vision : Industry Product · ISCA 2024 |
Methods — techniques the papers use, named apart from their topics
chiplet integration · 0.8advanced packaging · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | AMD Instinct MI300X Generative AI Accelerator and Platform Architectureabstract▪AMD Instinct™ MI300X Accelerator Overview ▪AMD CDNA™ 3 Architecture ▪Memory System Overview ▪Spatial Partitioning ▪4th Gen Infinity Architecture ▪System Architecture ▪AMD Instinct™ MI300X Platform ▪Application Performance Alan Smith 0003, Vamsi Alla |
HCS | 2 |
| 2024 | Realizing the AMD Exascale Heterogeneous Processor Vision : Industry ProductabstractAMD had previously detailed its exascale research journey from initial targets and requirements to the development and evolution of its vision of a high-performance computing (HPC) accelerated processing unit (APU), dubbed the Exascale Heterogeneous Processor or EHP. At the conclusion of that work, the learnings were integrated into the design of the node architecture that went into the Frontier supercomputer, the world’s first exascale machine. However, while the Frontier node architecture embodied many of the attributes of the EHP concept, advanced heterogeneous integration capabilities at the time were not yet sufficiently mature to realize our vision of a fully-integrated APU for HPC and AI. In this paper, we finish the EHP’s story by digging deeper into why an APU was not the right solution at the time of our first exascale architecture, what the shortcomings were of previous EHP concepts, and how AMD further evolved the concept into the AMD Instinct™ MI300A APU. MI300A is the culmination of years of AMD developments in advanced packaging technologies, its APU hardware and software, and the next step in our highly effective chiplet strategy to not only deliver a groundbreaking design for exascale computing, but to also meet the demands of new large-language model and generative AI applications. Alan Smith 0003, Gabriel H. Loh, Michael J. Schulte, Mike Ignatowski, Samuel Naffziger, Mike Mantor, Nathan Kalyanasundharam, Vamsi Alla, Nicholas Malaya, Joseph L. Greathouse, Eric Chapman, Raja Swaminathan |
ISCA | 8 |