Optimizing the flash-RAM energy trade-off in deeply embedded systems

Deeply embedded systems often have the tightest constraints on energy consumption, requiring that they consume tiny amounts of current and run on batteries for years. However, they typically execute code directly from flash, instead of the more energy efficient RAM. We implement a novel compiler optimization that exploits the relative efficiency of RAM by statically moving carefully selected basic blocks from flash to RAM. Our technique uses integer linear programming, with an energy cost model to select a good set of basic blocks to place into RAM, without impacting stack or data storage. We evaluate our optimization on a common ARM microcontroller and succeed in reducing the average power consumption by up to 41% and reducing energy consumption by up to 22%, while increasing execution time. A case study is presented, where an application executes code then sleeps for a period of time. For this example we show that our optimization could allow the application to run on battery for up to 32% longer. We also show that for this scenario the total application energy can be reduced, even if the optimization increases the execution time of the code

An analytical performance model for the Spidergon NoC

Networks on chip (NoC) emerged as a promising alternative to bus-based interconnect networks to handle the increasing communication requirements of the large systems on chip. Employing an appropriate topology for a NoC is of high importance mainly because it typically trade-offs between cross-cutting concerns such as performance and cost. The spidergon topology is a novel architecture which is proposed recently for NoC domain. The objective of the spidergon NoC has been addressing the need for a fixed and optimized topology to realize cost effective multi-processor SoC (MPSoC) development [7]. In this paper we analyze the traffic behavior in the spidergon scheme and present an analytical evaluation of the average message latency in the architecture. We prove the validity of the analysis by comparing the model against the results produced by a discreteevent simulator

C/VHDL codesign for LHCb VELO zero suppression algorithms

We present a workflow to generate cycle-accurate C and VHDL code from one common description to accelerate and unify algorithm implementation and simulation for real-time DSP applications in particle detectors. We use Confluence as description language which compiles into C-code (for simulation) and VHDL code (for implementation on FPGAs). We demonstrate the improved portability and simulation speed while assuring bit- and cycle-accuracy. Our approach solves the problem of having to maintain two source codes (for simulation and implementation) in parallel and therefore minimizes workload and the danger of inconsistent models. This is crucial in an environment where algorithm implementation is expected to cycle through several design iterations

Instruction-Level Abstraction (ILA): A Uniform Specification for System-on-Chip (SoC) Verification

Modern Systems-on-Chip (SoC) designs are increasingly heterogeneous and contain specialized semi-programmable accelerators in addition to programmable processors. In contrast to the pre-accelerator era, when the ISA played an important role in verification by enabling a clean separation of concerns between software and hardware, verification of these "accelerator-rich" SoCs presents new challenges. From the perspective of hardware designers, there is a lack of a common framework for the formal functional specification of accelerator behavior. From the perspective of software developers, there exists no unified framework for reasoning about software/hardware interactions of programs that interact with accelerators. This paper addresses these challenges by providing a formal specification and high-level abstraction for accelerator functional behavior. It formalizes the concept of an Instruction Level Abstraction (ILA), developed informally in our previous work, and shows its application in modeling and verification of accelerators. This formal ILA extends the familiar notion of instructions to accelerators and provides a uniform, modular, and hierarchical abstraction for modeling software-visible behavior of both accelerators and programmable processors. We demonstrate the applicability of the ILA through several case studies of accelerators (for image processing, machine learning, and cryptography), and a general-purpose processor (RISC-V). We show how the ILA model facilitates equivalence checking between two ILAs, and between an ILA and its hardware finite-state machine (FSM) implementation. Further, this equivalence checking supports accelerator upgrades using the notion of ILA compatibility, similar to processor upgrades using ISA compatibility.Comment: 24 pages, 3 figures, 3 table

Optimizing the FPGA memory design for a Sobel edge detector

This research explored different memory systems on FPGA chips in order to show the various trade-offs involved with choosing one memory system over another. We explored the different memory components that are found on FPGA chips using the example of a Sobel edge detector. We demonstrated how the different FPGA chip’s memories affected I/O performance and area. By exploiting the trade-offs between these a designer should be able to find an optimal on-chip memory system for a given application. Given further study, we believe we can develop application-specific memory templates that can be used with a hardware compiler to generate optimal on-chip memory system

Design of Reconfigurable Crossbar Switch for BiNoC Router

this paper presents implementation of 10x10 reconfigurable crossbar switch (RCS) architecture for Dynamic Self-Reconfigurable BiNoC Architecture for Network On Chip. Its main purpose is to increase the performance, flexibility. This paper presents a VHDL based cycle accurate register transfer level model for evaluating the, Power and Area of reconfigurable cross bar switch in BiNoC architectures. We implemented a parameterized register transfer level design of reconfigurable crossbar switch (RCS) architecture. The design is parameterized on (i) size of packets, (ii) length and width of physical links, (iii) number, and depth of arbiters, and (iv) switching technique. The paper discusses in detail the architecture and characterization of the various reconfigurable crossbar switch (RCS) architecture components. The characterized values were integrated into the VHDL based RTL design to build the cycle accurate performance model. In this paper we show the result of simple 10x10 crossbar switch .The results include VHDL simulation of RCS on Xilinx ISE 13.1 software tool

Automatic microarchitectural pipelining

This paper presents a method for automatic microarchitectural pipelining of systems with loops. The original specification is pipelined by performing provably-correct transformations including conversion to a synchronous elastic form, early evaluation, inserting empty buffers, anti-tokens, and retiming. The design exploration is done by solving an optimization problem followed by simulation of solutions. The method is explained on a DLX microprocessor example. The impact of different microarchitectural parameters on the performance is analyzed.Peer ReviewedPostprint (published version

Performance estimation of embedded software with confidence levels

Since time constraints are a very critical aspect of an embedded system, performance evaluation can not be postponed to the end of the design flow, but it has to be introduced since its early stages. Estimation techniques based on mathematical models are usually preferred during this phase since they provide quite accurate estimation of the application performance in a fast way. However, the estimation error has to be considered during design space exploration to evaluate if a solution can be accepted (e.g., by discarding solutions whose estimated time is too close to constraint). Evaluate if the possible error can be significant analyzing a punctual estimation is not a trivial task. In this paper we propose a methodology, based on statistical analysis, that provides a prediction interval on the estimation and a confidence level on meeting a time constraint. This information can drive design space exploration reducing the number of solutions to be validated. The results show how the produced intervals effectively capture the estimation error introduced by a linear model