Titlebook: Embedded Computer Systems: Architectures, Modeling, and Simulation; 19th International C Dionisios N. Pnevmatikatos,Maxime Pelcat,Matthias

Instantaneous

Conference proceedings 2019tion, SAMOS 2019, held in Pythagorion, Samos, Greece, in July 2019..The 21 regular papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on system design space exploration; deep learning optimization; system security; multi/many-core

Crater

灰心丧气

A Latency-Optimized Hash-Based Digital Signature Accelerator for the Tactile Internet (XMSS). It is computationally expensive and thus contradicts low latency requirements. This paper proposes a latency-optimized accelerator for hash-based digital signature processing for the XMSS algorithm. Our architecture improves the latency of signing and verification into the sub-millisecond range.

FRAUD

Conference proceedings 2019scheduling; system energy and heat management; many-core communication; and electronic system-level design and verification. In addition there are 13 papers from three special sessions which were organized on topics of current interest: insights from negative results; machine learning implementations; and European projects..

一起

细微差别

https://doi.org/10.1007/978-3-642-82339-8heme to index the input set of each convolutional layer to its output value. Our experimental results show that for a YOLOv3-tiny CNN, it is possible to achieve a speedup up to 3.5. while reducing the energy consumption to 22% of the baseline with an accuracy loss of 7.4%.

Champion

Analogy

cancellous-bone

Scalable Optimal Greedy Scheduler for Asymmetric Multi-/Many-Core Processorsoptimal (under certain constraints) for asymmetric processors. The proposed scheduler, called ., improves throughput by 26% and reduces average response time by up to 45% when compared to the default . scheduler on . asymmetric multi-core.

inferno

0302-9743 re are 13 papers from three special sessions which were organized on topics of current interest: insights from negative results; machine learning implementations; and European projects..978-3-030-27561-7978-3-030-27562-4Series ISSN 0302-9743 Series E-ISSN 1611-3349