Related papers: Status of the apeNEXT project
Modern processors are increasingly featuring multiple cores, as well as support for hardware virtualization. While these processors are common in desktop and server-class computing, they are less prevalent in embedded and real-time systems.…
The design and implementation of Deep Learning (DL) models is currently receiving a lot of attention from both industrials and academics. However, the computational workload associated with DL is often out of reach for low-power embedded…
This document provides detailed information on the status of Advanced and Novel Accelerators techniques and describes the steps that need to be envisaged for their implementation in future accelerators, in particular for high energy physics…
Modern Graphics Processing Units (GPUs) are now considered accelerators for general purpose computation. A tight interaction between the GPU and the interconnection network is the strategy to express the full potential on capability…
Research on asynchronous cellular automata has received a great amount of attention these last years and has turned to a thriving field. We survey the recent research that has been carried out on this topic and present a wide state of the…
Efficiently serving Large Language Models (LLMs) requires selecting an optimal parallel execution plan, balancing computation, memory, and communication overhead. However, determining the best strategy is challenging due to varying…
Recently, Graphcore has introduced an IPU Processor for accelerating machine learning applications. The architecture of the processor has been designed to achieve state of the art performance on current machine intelligence models for both…
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently utilized technologies, providing an overview of emerging…
The past decade has seen a remarkable series of advances in machine learning, and in particular deep learning approaches based on artificial neural networks, to improve our abilities to build more accurate systems across a broad range of…
Prior work on Automatically Scalable Computation (ASC) suggests that it is possible to parallelize sequential computation by building a model of whole-program execution, using that model to predict future computations, and then…
This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, to perform high-throughput inference by exploiting the computation time-accuracy trade-off. Without the need for retraining, a…
In this paper, we describe the architecture and performance of the GRAPE-6 system, a massively-parallel special-purpose computer for astrophysical $N$-body simulations. GRAPE-6 is the successor of GRAPE-4, which was completed in 1995 and…
We report on the status of the Fermilab accelerator complex, including recent performance, upgrades in progress, and plans for the future. Beam delivery to the neutrino experiments surpassed our goals for the past year. The Proton…
Quantum computers, if fully realized, promise to be a revolutionary technology. As a result, quantum computing has become one of the hottest areas of research in the last few years. Much effort is being applied at all levels of the system…
With growing computational needs of many real-world applications, frequently changing specifications of standards, and the high design and NRE costs of ASICs, an algorithm-agile FPGA based co-processor has become a viable alternative. In…
The paper is devoted to the problem of mapping affine loop nests onto distributed memory parallel computers. A method to find affine transformations of loop nests for parallel execution and distribution of data over processors is presented.…
Quantum computing is presently undergoing rapid development to achieve a significant speedup promised in certain applications. Nonetheless, scaling quantum computers remains a formidable engineering challenge, prompting exploration of…
Manycore System-on-Chip include an increasing amount of processing elements and have become an important research topic for improvements of both hardware and software. While research can be conducted using system simulators, prototyping…
Exascale systems, expected to emerge by the end of the next decade, will require the exploitation of billion-way parallelism at multiple hierarchical levels in order to achieve the desired sustained performance. The task of assessing future…
We define a benchmark suite for lattice QCD and report on benchmark results from several computer platforms. The platforms considered are apeNEXT, CRAY T3E, Hitachi SR8000, IBM p690, PC-Clusters, and QCDOC.