58 research outputs found
CROSS-LAYER DESIGN, OPTIMIZATION AND PROTOTYPING OF NoCs FOR THE NEXT GENERATION OF HOMOGENEOUS MANY-CORE SYSTEMS
This thesis provides a whole set of design methods to enable and manage the
runtime heterogeneity of features-rich industry-ready Tile-Based Networkon-
Chips at different abstraction layers (Architecture Design, Network Assembling,
Testing of NoC, Runtime Operation). The key idea is to maintain
the functionalities of the original layers, and to improve the performance
of architectures by allowing, joint optimization and layer coordinations. In
general purpose systems, we address the microarchitectural challenges by codesigning
and co-optimizing feature-rich architectures. In application-specific
NoCs, we emphasize the event notification, so that the platform is continuously
under control. At the network assembly level, this thesis proposes a
Hold Time Robustness technique, to tackle the hold time issue in synchronous
NoCs. At the network architectural level, the choice of a suitable synchronization
paradigm requires a boost of synthesis flow as well as the coexistence
with the DVFS. On one hand this implies the coexistence of mesochronous
synchronizers in the network with dual-clock FIFOs at network boundaries.
On the other hand, dual-clock FIFOs may be placed across inter-switch links
hence removing the need for mesochronous synchronizers. This thesis will
study the implications of the above approaches both on the design flow and
on the performance and power quality metrics of the network. Once the manycore
system is composed together, the issue of testing it arises. This thesis
takes on this challenge and engineers various testing infrastructures. At the
upper abstraction layer, the thesis addresses the issue of managing the fully
operational system and proposes a congestion management technique named
HACS. Moreover, some of the ideas of this thesis will undergo an FPGA
prototyping. Finally, we provide some features for emerging technology by
characterizing the power consumption of Optical NoC Interfaces
Driving the Network-on-Chip Revolution to Remove the Interconnect Bottleneck in Nanoscale Multi-Processor Systems-on-Chip
The sustained demand for faster, more powerful chips has been met by the
availability of chip manufacturing processes allowing for the integration of increasing
numbers of computation units onto a single die. The resulting outcome,
especially in the embedded domain, has often been called SYSTEM-ON-CHIP
(SoC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MP-SoC).
MPSoC design brings to the foreground a large number of challenges, one of
the most prominent of which is the design of the chip interconnection. With a
number of on-chip blocks presently ranging in the tens, and quickly approaching
the hundreds, the novel issue of how to best provide on-chip communication
resources is clearly felt.
NETWORKS-ON-CHIPS (NoCs) are the most comprehensive and scalable
answer to this design concern. By bringing large-scale networking concepts to
the on-chip domain, they guarantee a structured answer to present and future
communication requirements. The point-to-point connection and packet switching
paradigms they involve are also of great help in minimizing wiring overhead
and physical routing issues. However, as with any technology of recent inception,
NoC design is still an evolving discipline. Several main areas of interest
require deep investigation for NoCs to become viable solutions:
• The design of the NoC architecture needs to strike the best tradeoff among
performance, features and the tight area and power constraints of the onchip
domain.
• Simulation and verification infrastructure must be put in place to explore,
validate and optimize the NoC performance.
• NoCs offer a huge design space, thanks to their extreme customizability in
terms of topology and architectural parameters. Design tools are needed
to prune this space and pick the best solutions.
• Even more so given their global, distributed nature, it is essential to evaluate
the physical implementation of NoCs to evaluate their suitability for
next-generation designs and their area and power costs.
This dissertation performs a design space exploration of network-on-chip architectures,
in order to point-out the trade-offs associated with the design of
each individual network building blocks and with the design of network topology
overall. The design space exploration is preceded by a comparative analysis
of state-of-the-art interconnect fabrics with themselves and with early networkon-
chip prototypes. The ultimate objective is to point out the key advantages
that NoC realizations provide with respect to state-of-the-art communication
infrastructures and to point out the challenges that lie ahead in order to make
this new interconnect technology come true. Among these latter, technologyrelated
challenges are emerging that call for dedicated design techniques at all
levels of the design hierarchy. In particular, leakage power dissipation, containment
of process variations and of their effects. The achievement of the above
objectives was enabled by means of a NoC simulation environment for cycleaccurate
modelling and simulation and by means of a back-end facility for the
study of NoC physical implementation effects. Overall, all the results provided
by this work have been validated on actual silicon layout
Process-variation aware mapping of real-time streaming applications to MPSoCs for improved yield
Abstract—As technology scales, the impact of process variation on the maximum supported frequency (FMAX) of individual cores in a MPSoC becomes more pronounced. Task allocation without variation-aware performance analysis can result in a significant loss in yield, defined as the number of manufactured chips satisfying the application timing requirement. We propose variation-aware task allocation for real-time streaming applica-tions modeled as task graphs. Our solutions are primarily based on the throughput requirement, which is the most important timing requirement in many real-time streaming applications. The three main contributions of this paper are: 1) Using data flow graphs that are well-suited for modeling and analysis of real-time streaming applications, we explicitly model task execution both in terms of clock cycles (which is independent of variation) and seconds (which does depend on the variation of the resource), which we connect by an explicit binding. 2) We present two approaches for optimizing the yield. The approaches give different results at different costs. 3) We present exhaustive and heuristic algorithms that implement the optimization approaches. Our variation-aware mapping algorithms are tested on models of real applications, and are compared to the mapping methods that are unaware of hardware variation. Our results demonstrate yield improvements of up to 50 % with an average of 31%, showing the effectiveness of our approaches. Index Terms—Process variation, Multiprocessor System-on
Multi-Softcore Architecture on FPGA
To meet the high performance demands of embedded multimedia applications, embedded systems are integrating multiple processing units. However, they are mostly based on custom-logic design methodology. Designing parallel multicore systems using available standards intellectual properties yet maintaining high performance is also a challenging issue. Softcore processors and field programmable gate arrays (FPGAs) are a cheap and fast option to develop and test such systems. This paper describes a FPGA-based design methodology to implement a rapid prototype of parametric multicore systems. A study of the viability of making the SoC using the NIOS II soft-processor core from Altera is also presented. The NIOS II features a general-purpose RISC CPU architecture designed to address a wide range of applications. The performance of the implemented architecture is discussed, and also some parallel applications are used for testing speedup and efficiency of the system. Experimental results demonstrate the performance of the proposed multicore system, which achieves better speedup than the GPU (29.5% faster for the FIR filter and 23.6% faster for the matrix-matrix multiplication)
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