[hpc-announce] IEEE/SBC 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2024) External Inbox

[J Nelson Amaral]

The IEEE/SBC 36th International Symposium on Computer Architecture and
High Performance Computing (SBAC-PAD 2024) will take place from
November 13 to 15, at the Hilo Hawaiian Hotel in Hawaii, USA.

https://urldefense.us/v3/__https://sites.google.com/ime.usp.br/sbac2024__;!!G_uCfscf7eWS!eByP6qdkDMMDZkQricuzUedzsqdrxX95lQEvVrVLve65-Wu1hkngaYk7voIsKAjsw-FJ1aemFCcuTvVC6sUk72vm3g$ 

SBAC-PAD is an annual international conference series, which presents
the latest trends, current research and developments, and novel tools
and applications in the fields of Computer Architecture,
High-Performance Computing, and Parallel and Distributed Computing
technologies. SBAC-PAD is open to industry, faculty, researchers,
practitioners, and undergraduate and graduate students from around the
world. Its scientific program is composed of high-quality submitted
papers, selected by a thorough peer review process, and invited talks
from renowned researchers.

***** Important dates
Abstract submission deadline    July 16th, 2024 AoE (FIRM)
Paper submission deadline       July 16th, 2024 AoE (FIRM)
Rebuttal period August 19 — August 22, 2024
Author notification     September 02, 2024
Camera-ready submission September 23, 2024
The program committee will select the top-ranked papers as finalists,
and one paper will be selected during the conference as the Best
Paper. Selected papers will also be invited to submit an extended
version to a special issue of the Journal of Parallel and Distributed
Computing.

***** Topics of Interest
Authors are invited to submit original manuscripts to one of five
tracks that address challenges in any of the following areas related
to the fields of Computer Architecture (CA) and High-performance and
Distributed Computing (HPDC). Topics of interest include (but are not
limited to):

Application-specific systems;
Architecture and programming support for emerging domains: Big Data,
Deep Learning, Machine learning, Cognitive Systems;
Artificial intelligence and machine learning methods for CA and HPDC,
and CA and HPDC for Artificial intelligence applications;
Benchmarking, performance modeling, analysis, and evaluation;
Blockchain and distributed ledgers;
Cloud, cluster, and edge/fog computing systems;
Data-intensive workloads and tools;
Data management, storage, and I/O;
Embedded and pervasive systems;
GPUs, FPGAs, and accelerator architectures;
Languages, compilers, and tools for parallel and distributed programming;
Modeling and simulation methodologies;
Operating systems and virtualization;
Parallel and distributed systems, algorithms, models, and applications;
Power and energy-efficient systems;
Predictive models to improve performance of scientific applications
Processing-in-memory or near-data processing technologies
Processor, cache, memory, storage, and network architecture;
Quantum computing in CA and HPDC;
Real-world applications and case studies;
Reconfigurable, resilient, and fault-tolerant systems;
Security and privacy in CA and HPDC;
Workflow systems.