Results 21 to 30 of about 193,534 (289)
Code Transpilation for Hardware Accelerators
CoRR, 2023 DSLs and hardware accelerators have proven to be very effective in optimizing computationally expensive workloads. In this paper, we propose a solution to the challenge of manually rewriting legacy or unoptimized code in domain-specific languages and hardware accelerators. We introduce an approach that integrates two open-source tools: Metalift, a code
Yuto Nishida +5 more
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Hardware acceleration architectures for MPEG-Based mobile video platforms: a brief overview [PDF]
, 2003 This paper presents a brief overview of past and current hardware acceleration (HwA) approaches that have been proposed for the most computationally intensive compression tools of the MPEG-4 standard.
Kinane, Andrew +5 more
core +2 more sources
Hardware Acceleration of Neural Graphics
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023 Rendering and inverse-rendering algorithms that drive conventional computer graphics have recently been superseded by neural representations (NR). NRs have recently been used to learn the geometric and the material properties of the scenes and use the information to synthesize photorealistic imagery, thereby promising a replacement for traditional ...
Muhammad Husnain Mubarik +3 more
openaire +2 more sources
Towards hardware acceleration of neuroevolution for multimedia processing applications on mobile devices [PDF]
, 2006 This paper addresses the problem of accelerating large artificial neural networks (ANN), whose topology and weights can evolve via the use of a genetic algorithm.
A.R. Omondi +10 more
core +1 more source
Hardware Accelerated Power Estimation [PDF]
Design, Automation and Test in Europe, 2005 In this paper, we present power emulation, a novel design paradigm that utilizes hardware acceleration for the purpose of fast power estimation. Power emulation is based on the observation that the functions necessary for power estimation (power model evaluation, aggregation, etc.) can be implemented as hardware circuits.
Joel Coburn +2 more
openaire +3 more sources
Hardware Acceleration of Number Theoretic Transform in zk-SNARK [PDF]
Jisuanji kexue yu tansuoThe proof in zk-SNARK has a fixed length and can be verified quickly, promoting the application of zero-knowledge proof in areas such as digital signature, blockchain, distributed storage, and outsourced computing.
ZHAO Haixu, CHAI Zhilei, HUA Pengcheng, WANG Feng, DING Dong
doaj +1 more source
Investigating hardware acceleration for simulation of CFD quantum circuits
Frontiers in Mechanical Engineering, 2022 Among the many computational models for quantum computing, the Quantum Circuit Model is the most well-known and used model for interacting with current quantum hardware.
Youssef Moawad +2 more
doaj +1 more source
Hardware Accelerators in Autonomous Driving
CoRR, 2023 Computing platforms in autonomous vehicles record large amounts of data from many sensors, process the data through machine learning models, and make decisions to ensure the vehicle's safe operation. Fast, accurate, and reliable decision-making is critical.
Ken Power +4 more
openaire +2 more sources
Integration of a mean-torque diesel engine model into a hardware-in-the-loop shipboard network simulation using lambda tuning [PDF]
, 2011 This study describes the creation of a hardware-in-the-loop (HIL) environment for use in evaluating network architecture, control concepts and equipment for use within marine electrical systems.
Burt, G. M. +3 more
core +1 more source
Custom Hardware Inference Accelerator for TensorFlow Lite for Microcontrollers
IEEE Access, 2022 In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has been steadily increasing. However, the high computational demand required for Machine Learning (ML) inference on tiny microcontroller-based IoT devices ...
Erez Manor, Shlomo Greenberg
doaj +1 more source