Pedro Petersen Moura Trancoso
Visar 32 publikationer
RAINBOW: Multi-Dimensional Hardware-Software Co-Design for DL Accelerator On-Chip Memory
Evaluation of heterogeneous AIoT Accelerators within VEDLIoT
EVALUATION OF HETEROGENEOUS AIOT ACCELERATORS WITHIN VEDLIOT
VEDLIoT: Next generation accelerated AIoT systems and applications
eProcessor: European, Extendable, Energy-Efficient, Extreme-Scale, Extensible, Processor Ecosystem
ARADA: Adaptive Resource Allocation for Improving Energy Efficiency in Deep Learning Accelerators
FiBHA: Fixed Budget Hybrid CNN Accelerator
VSA: A Hybrid Vector-Systolic Architecture
Introduction to the Special Section on FPL 2020
VEDLIoT: very efficient deep learning in IoT
VEDLIoT: Very Efficient Deep Learning in IoT
Reliability Analysis of Compressed CNNs
LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
Hybrid2: Combining Caching and Migration in Hybrid Memory Systems
Mapping Multiple LSTM models on FPGAs
AVR: Reducing Memory Traffic with Approximate Value Reconstruction
Energy-efficient Runtime Management of Heterogeneous Multicores using Online Projection
Decoupled fused cache: Fusing a decoupled LLC with a DRAM cache
LLC-guided data migration in hybrid memory systems
Time-SWAD: A dataflow engine for time-based single window stream aggregation
FusionCache: Using LLC tags for DRAM cache
LEGaTO: First Steps Towards Energy-Efficient Toolset for Heterogeneous Computing
LEGaTO: Towards Energy-Efficient, Secure, Fault-tolerant Toolset for Heterogeneous Computing
Single Window Stream Aggregation using Reconfigurable Hardware
Using personality metrics to improve cache interference management in multicore processors
PHOENIX: Efficient computation in memory
SWAS: Stealing Work Using Approximate System-Load Information
Heterogeneous- and NUMA-aware scheduling for many-core architectures
SWITCHES: A Lightweight Runtime for Dataflow Execution of Tasks on Many-Cores
Odd-ECC: On-demand DRAM error correcting codes
Low-Cost Sub-5W Processors for Edge HPC
Auto-tuning Static Schedules for Task Data-flow Applications
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Visar 8 forskningsprojekt
AutoPIM,: Effektiv accelerator för autonoma fordon
Pilot using Independent Local & Open Technologies (The European PILOT)
Principer för beräknande minnesenheter (PRIDE)
Very Efficient Deep Learning in IOT (VEDLIoT)
PRIME: Konstruktionsprinciper för minnesberäknande parallella system