Related papers: Supporting CUDA for an extended RISC-V GPU archite…

The RVfpga course offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and the VeeR EL2, developed…

GPUs have become the dominant source of computing power for high performance computing and are increasingly being used across the High Energy Physics computing landscape for a wide variety of tasks. Though NVIDIA is currently the main…

Progress in quantum computing hardware raises questions about how these devices can be controlled, programmed, and integrated with existing computational workflows. We briefly describe several prominent quantum computational models, their…

This paper assesses and reports the experience of ten teams working to port,validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC…

RISC-V is a recently developed open instruction set architecture gaining a lot of attention. To achieve a lasting security on these systems and design efficient countermeasures, a better understanding of vulnerabilities to novel and…

Open-source EDA shows promising potential in unleashing EDA innovation and lowering the cost of chip design. This paper presents an open-source EDA project, iEDA, aiming for building a basic infrastructure for EDA technology evolution and…

RISC-V, an open instruction set architecture, is getting the attention of soft processor developers. Implementing only a basic 32-bit integer instruction set of RISC-V, which is defined as RV32I, might be satisfactory for embedded systems.…

In recent history, GPUs became a key driver of compute performance in HPC. With the installation of the Frontier supercomputer, they became the enablers of the Exascale era; further largest-scale installations are in progress (Aurora, El…

For years, SIMD/vector units have enhanced the capabilities of modern CPUs in High-Performance Computing (HPC) and mobile technology. Typical commercially-available SIMD units process up to 8 double-precision elements with one instruction.…

The emergence of heterogeneity and domain-specific architectures targeting deep learning inference show great potential for enabling the deployment of modern CNNs on resource-constrained embedded platforms. A significant development is the…

Low bit-width Quantized Neural Networks (QNNs) enable deployment of complex machine learning models on constrained devices such as microcontrollers (MCUs) by reducing their memory footprint. Fine-grained asymmetric quantization (i.e.,…

Increased attention to RISC-V in Cloud, Data Center, Automotive and Networking applications, has been fueling the move of RISC-V to the high-performance computing scenario. However, lack of powerful performance monitoring tools will result…

Security in modern RISC-V processors demands more than functional correctness: It requires resilience to side-channel attacks. This paper evaluates the vulnerability of the side channel of the CVA6 RISC-V core by analyzing software-based…

Our goal in this paper is to understand how to maximize energy efficiency when designing standard-ISA processor cores for subthreshold operation. We hence develop a custom subthreshold library and use it to synthesize the open-source RISC-V…

This paper presents a novel System-on-Chip (SoC) architecture for accelerating complex deep learning models for edge computing applications through a combination of hardware and software optimisations. The hardware architecture tightly…

RISC-V is a promising open-source architecture primarily targeted for embedded systems. Programs compiled using the RISC-V toolchain can run bare-metal on the system, and, as such, can be vulnerable to several memory corruption…

This paper introduces a novel 32-bit microprocessor, based on the RISC-V instruction set architecture, is designed,utilising a dynamic clock source to achieve high efficiency, overcoming the limitations of hardware delays. In addition, the…

Edge AI inference is becoming prevalent thanks to the emergence of small yet high-performance microprocessors. This shift from cloud to edge processing brings several benefits in terms of energy savings, improved latency, and increased…

Vitamin-V is a project funded under the Horizon Europe program for the period 2023-2025. The project aims to create a complete open-source software stack for RISC-V that can be used for cloud services. This software stack is intended to…

The current trend of technology has brought parallel machines equipped with multiple processors and multiple memory sockets to be available off-the-shelf -- or via renting through Iaas Clouds -- at reasonable costs. This has opened the…