【CFP】CGRA4HPCA: HPC&AI向け粗粒度再構成可能アーキに関する国際WS（2/17締切延長, IPDPS併設）

[Kentaro Sano]

SWoPP-MLの皆様

理研の佐野です。HPCおよびAI向けの粗粒度再構成可能アレイ(CGRA)に関するIPDPS併設
国際ワークショップ(CGRA4HPC)の投稿締切が延長されたので、ご案内します。

CGRA4HPCA 2026 (https://cgra4hpca.github.io/)
Where: New Orleans, USA
When : May 25, 2026
Submission Link:
https://ssl.linklings.net/conferences/ipdps/?page=Submit&id=CGRA4HPCWorkshopFullSubmission&site=ipdps2026

Important Deadlines:
Paper submission : Feb 17, 2026 (EXTENDED)
Camera-ready due : Mar 6, 2026

皆さまの投稿をお待ちしております。
どうぞよろしくお願い致します。

--
佐野


[IPDPS] [Deadline Extended] Call For Papers (CFP): The Fifth
International Workshop on Coarse-Grained Reconfigurable Architectures
for High-Performance Computing and AI (CGRA4HPCA'26)


We are happy to welcome submissions to the the Fifth International
Workshop on Coarse-Grained Reconfigurable Architectures for
High-Performance Computing and AI (CGRA4HPCA), held in conjunction
with IPDPS 2026.

----------------------- GENERAL INFORMATION -------------------------

CGRA4HPCA 2026 will be held in conjunction with IPDPS 2026 in New
Orleans, USA, on May 25th.

Where: New Orleans, USA
When: May 25th
Website: https://cgra4hpca.github.io/
Submission Link:
https://ssl.linklings.net/conferences/ipdps/?page=Submit&id=CGRA4HPCWorkshopFullSubmission&site=ipdps2026

Important Deadlines:
Paper submission: February 17th, 2026 (EXTENDED)
Camera-ready due: March 6th, 2026

-------------------------- DESCRIPTION ------------------------------
Coarse-grained reconfigurable arrays (CGRAs) are programmable logic
devices that offer plasticity/reconfigurability, albeit at a
coarse-grained (word-configurable) level in comparison to fine-grained
FPGAs.
Such reconfigurability allows the silicon to be specialized towards a
particular application in order to reduce data movement and improve
performance and energy efficiency. Unlike their cousins, the
Field-Programmable Gate Arrays (FPGAs),
CGRAs provide reconfigurable Arithmetic Logic Units (ALUs) and a
highly specialized yet versatile data path. This ``coarsening'' of
reconfiguration allows CGRAs to achieve a significant (custom
ASIC-like) reduction in power consumption and
increase in operating frequency compared to FPGAs. At the same time,
they remedy and overcome the expensive von Neumann
(instruction-decoding) overhead that traditional general-purpose
processors (CPUs) suffer from. In short, CGRAs
strike a seemingly perfect balance between the reconfigurability of
FPGAs and the performance of CPUs, with power-consumption
characteristics closer to custom ASICs.

The International Workshop on Coarse-Grained Reconfigurable
Architectures for High-Performance Computing and AI (CGRA4HPCA)
aspires to provide a recurring forum for HPC experts and CGRA hardware
researchers from academia or industry to come together and discuss
state-of-the-art CGRA research for use in emerging HPC systems and AI.

----------------------- TOPICS OF INTEREST -------------------------
Topics of interest include (but are not limited to):

- Novel high-performance CGRA architectures for HPC and AI, including
energy-efficient architectures(incl. asynchronous/clockless CGRAs,
powerconsumption optimizations, etc.)
- Parallel programming language support for programming CGRA
architectures (e.g., supporting OpenMP or CUDA/HIP for programming
CGRA architectures)
- Compilation strategies, algorithms, and methods for mapping
computations and applications onto CGRAs
- Smart middleware and runtime systems for support of CGRAs, including
multi-CGRA systems for HPC and AI
- Experience in porting scientific kernels and applications to
state-of-the-art CGRAs (e.g., weather/climate codes, CFD, MD, etc.)
- The use of CGRA frameworks (e.g., CGRA-ME and OpenCGRA) to generate
and customize architectures
- Software-programmable CGRAs (e.g., Xilinx ACAP Versal)
- Processors with a tightly interconnected CGRA subsystem
- Machine Learning applications and case studies, performance and
power-efficiency comparisons between traditional systems (CPUs/GPUs)
and CGRAs
- Combination of CGRAs and other emerging post-Moore models (e.g.,
neuromorphic systems)
- New emerging CGRA-like architectures for Generative AI
- Case studies and evaluations of CGRAs for (Generative) AI
- AI and Machine Learning applications and casestudies, performance
and power-efficiency comparisons between traditional systems
(CPUs/GPUs) and CGRAs

New for this year:
- Architectures, applications, and use-cases of CGRAs and AI to Edge
computing, and
- Architectures, applications, and use-cases of CGRAs and AI to compute in Space

-------------------------- SUBMISSION ------------------------------
We welcome authors to contribute full-length research papers subject
to the topics of interest described above. Contributions should be
unpublished and not for consideration in other venues. We will adopt a
single-blind review process for all papers. Papers should not exceed
eight (8) single-spaced pages, formatted in the double-column pages
using 10-point size font on 8.5x11 inch pages (IEEE conference style).
Accepted papers will be included in the workshop proceedings, that
will be distributed at the conference and are submitted for inclusion
in the IEEE Xplore Digital Library after the conference.

We also welcome presentations on new and emerging CGRA technologies
from industry and startups. These will be presented at a special
lightning session in the workshop. Please contact the workshop
organizers (pod...@kth.se) if you are interested in participating in
this event.

----------------------- ORGANIZATION -------------------------
ORGANIZERS:
Artur Podobas (KTH, Sweden)
Kentaro Sano (RIKEN, Japan)
Jason Anderson (University of Toronto, Canada)
Tomohiro Ueno (RIKEN, Japan)

Program Committee
Boma Anantasatya Adhi, RIKEN
Cheng Tan, Google/ASU
Christian Hochberger, TU Darmstadt
Georgi Gaydadjiev, TU Delft
Jens Domke, RIKEN CCS
Lingli Wang, Fudan Univ
Markus Weinhardt, HS Osnabruck
Takuya Kojima, Univ. of Tokyo