A survey on deep learning hardware accelerators for heterogeneous hpc platforms
Recent trends in deep learning (DL) imposed hardware accelerators as the most viable
solution for several classes of high-performance computing (HPC) applications such as …
solution for several classes of high-performance computing (HPC) applications such as …
Test-driving RISC-V Vector hardware for HPC
Abstract Whilst the RISC-V Vector extension (RVV) has been ratified, at the time of writing
both hardware implementations and open source software support are still limited for …
both hardware implementations and open source software support are still limited for …
Efficient execution of SpGEMM on long vector architectures
V Le Fèvre, M Casas - … of the 32nd International Symposium on High …, 2023 - dl.acm.org
The Sparse GEneral Matrix-Matrix multiplication (SpGEMM) C= A x B is a fundamental
routine extensively used in domains like machine learning or graph analytics. Despite its …
routine extensively used in domains like machine learning or graph analytics. Despite its …
Spatz: Clustering compact RISC-V-based vector units to maximize computing efficiency
The ever-increasing computational and storage requirements of modern applications and
the slowdown of technology scaling pose major challenges to designing and implementing …
the slowdown of technology scaling pose major challenges to designing and implementing …
Software Development Vehicles to enable extended and early co-design: a RISC-V and HPC case of study
Prototyping HPC systems with low-to-mid technology readiness level (TRL) systems is
critical for providing feedback to hardware designers, the system software team (eg …
critical for providing feedback to hardware designers, the system software team (eg …
IndexMAC: A Custom RISC-V Vector Instruction to Accelerate Structured-Sparse Matrix Multiplications
V Titopoulos, K Alexandridis, C Peltekis… - … , Automation & Test …, 2024 - ieeexplore.ieee.org
Structured sparsity has been proposed as an efficient way to prune the complexity of modern
Machine Learning (ML) applications and to simplify the handling of sparse data in hardware …
Machine Learning (ML) applications and to simplify the handling of sparse data in hardware …
Yun: An open-source, 64-bit RISC-V-Based vector processor with multi-precision integer and floating-point support in 65-nm CMOS
The nature and heterogeneity of modern workloads force hardware designers to choose
between general-purpose processors, which come with superior flexibility, and highly …
between general-purpose processors, which come with superior flexibility, and highly …
QUETZAL: Vector Acceleration Framework for Modern Genome Sequence Analysis Algorithms
Genome sequence analysis is fundamental to medical breakthroughs such as developing
vaccines, enabling genome editing, and facilitating personalized medicine. The …
vaccines, enabling genome editing, and facilitating personalized medicine. The …
Short reasons for long vectors in HPC CPUs: a study based on RISC-V
P Vizcaino, G Ieronymakis, N Dimou… - Proceedings of the SC' …, 2023 - dl.acm.org
For years, SIMD/vector units have enhanced the capabilities of modern CPUs in High-
Performance Computing (HPC) and mobile technology. Typical commercially-available …
Performance Computing (HPC) and mobile technology. Typical commercially-available …
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks
C Zhou, V Richard, P Savarese, Z Hassman… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent advancements in quantization and mixed-precision techniques offer significant
promise for improving the run-time and energy efficiency of neural networks. In this work, we …
promise for improving the run-time and energy efficiency of neural networks. In this work, we …