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Jacob Queiser

dblp:421/2247 · also Jake Queiser · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0006-6421-2768ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 2 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
Reconfigurable computing and FPGAs · 33% High-performance computing · 33% Hardware accelerators and domain-specific architectures · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing
collective communication
0.912025
A Streaming Collectives Interface Targeting Dataflow Acceleration and HPC Workloads · SC 2025
Hardware accelerators and domain-specific architectures › spatial architecture
dataflow accelerator
0.912025
A Streaming Collectives Interface Targeting Dataflow Acceleration and HPC Workloads · SC 2025
Reconfigurable computing and FPGAs
FPGA accelerator
0.912025
A Streaming Collectives Interface Targeting Dataflow Acceleration and HPC Workloads · SC 2025

Methods — techniques the papers use, named apart from their topics

software-hardware co-design · 0.9high-level synthesis · 0.9
YearPublicationVenuePosition
2026 Design and Implementation of Casting Compression for GPU-Aware MPI Collectives
Chen-Chun Chen, Nicholas Contini, Jacob Queiser, Hari Subramoni, Dhabaleswar K. Panda 0001
IPDPS4
2025 A Streaming Collectives Interface Targeting Dataflow Acceleration and HPC Workloads
abstract
Dataflow accelerators can provide energy efficient and high-performance alternatives to current popular architectures. However, little work has been done to enable accelerator-initiated, scalable collective communication for these architectures. We develop a High Level Synthesis (HLS) interface to bridge this gap through software-hardware co-design. Given the tendency of dataflow applications to use reads and writes to streams to express data transfer, we develop a streaming interface implementing fine-grained transfers to the host processor. Data can then be communicated through MPI and transferred to the receiving accelerator. As a result, the interface uses few hardware resources for communication. As a case study, we enhance the HPL benchmark from HPCC_FPGA with our contributions. We evaluate our final design on up to 16 FPGAs, achieving up to 18% improvement in application throughput and 36% reduced latency in kernel execution. Additionally, we design a stencil benchmark that showcases superlinear speedup in a strong scaling scenario.
Nicholas Contini, Jacob Queiser, Bharath Ramesh 0005, Hari Subramoni, Dhabaleswar K. Panda 0001
SC2