Adaptive Latency Insensitive Protocols andElastic Circuits with Early Evaluation: A Comparative Analysis

AbstractLatency Insensitive Protocols (LIP) and Elastic Circuits (EC) solve the same problem of rendering a design tolerant to additional latencies caused by wires or computational elements. They are performance-limited by a firing semantics that enforces coherency through a lazy evaluation rule: Computation is enabled if all inputs to a block are simultaneously available. Adaptive LIP's (ALIP) and EC with early evaluation (ECEE) increase the performance by relaxing the evaluation rule: Computation is enabled as soon as the subset of inputs needed at a given time is available. Their difference in terms of implementation and behavior in selected cases justifies the need for the comparative analysis reported in this paper. Results have been obtained through simple examples, a single representative case-study already used in the context of both LIP's and EC and through extensive simulations over a suite of benchmarks

Performance optimization of elastic systems using buffer resizing and buffer insertion

Buffer resizing and buffer insertion are two transformation techniques for the performance optimization of elastic systems. Different approaches for each technique have already been proposed in the literature. Both techniques increase the storage capacity and can potentially contribute to improve the throughput of the system. Each technique offers a different trade-off between area cost and latency. This paper presents a method that combines both techniques to achieve the maximum possible throughput while minimizing the cost of the implementation. The provided method is based on mixed integer linear programming. A set of experiments is designed to show the feasibility of the approach.Peer ReviewedPostprint (published version

Topology-Based Performance Analysis and Optimization of Latency-Insensitive Systems

Latency-insensitive protocols allow system-on-chip engineers to decouple the design of the computing cores from the design of the inter-core communication channels while following the synchronous design paradigm. In a latency-insensitive system (LIS) each core is encapsulated within a shell, a synthesized interface module that dynamically controls its operation. At each clock period, if new data has not arrived on an input channel or a stalling request has arrived on an output channel, the shell stalls the core and buffers other incoming valid data for future processing. The combination of finite buffers and backpressure from stalling can cause throughput degradation. Previous works addressed this problem by increasing buffer space to reduce the backpressure requests or inserting extra buffering to balance the channel latency around a LIS. We explore the theoretical complexity of these approaches and propose a heuristic algorithm for efficient queue sizing. We also practically characterize several LIS topologies and how the topology of a LIS can impact not only how much throughput degradation will occur, but also the difficulty of finding optimal queue sizing solutions

Topology-based optimization of maximal sustainable throughput in a latency-insensitive system

We consider the problem of optimizing the performance of a latency-insensitive system (LIS) where the addition of backpressure has caused throughput degradation. Previous works have addressed the problem of LIS performance in different ways. In particular, the insertion of relay stations and the sizing of the input queues in the shells are the two main optimization techniques that have been proposed. We provide a unifying framework for this problem by outlining which approaches work for different system topologies, and highlighting counterexamples where some solutions do not work. We also observe that in the most difficult class of topologies, instances with the greatest throughput degradation are typically very amenable to simplifications. The contributions of this paper include a characterization of topologies that maintain optimal throughput with fixedsize queues and a heuristic for sizing queues that produces solutions close to optimal in a fraction of the time

Doctor of Philosophy

dissertationElasticity is a design paradigm in which circuits can tolerate arbitrary latency/delay variations in their computation units as well as communication channels. Creating elastic (both synchronous and asynchronous) designs from clocked designs has potential benefits of increased modularity and robustness to variations. Several transformations have been suggested in the literature and each of these require a handshake control network (examples include synchronous elasticization and desynchronization). Elastic control network area and power overheads may become prohibitive. This dissertation investigates different optimization avenues to reduce these overheads without sacrificing the control network performance. First, an algorithm and a tool, CNG, is introduced that generates a control network with minimal total number of join and fork control steering units. Synchronous Elastic FLow (SELF) is a handshake protocol used over synchronous elastic designs. Comparing to its standard eager implementation (that uses eager forks - EForks), lazy SELF can consume less power and area. However, it typically suff ers from combinational cycles and can have inferior performance in some systems. Hence, lazy SELF has been rarely studied in the literature. This work formally and exhaustively investigates the specifi cations, diff erent implementations, and verifi cation of the lazy SELF protocol. Furthermore, several new and existing lazy designs are mapped to hybrid eager/lazy imple-mentations that retain the performance advantage of the eager design but have power and area advantages of lazy implementations, and are combinational-cycle free. This work also introduces a novel ultra simple fork (USFork) design. The USFork has two advantages over lazy forks: it is composed of simpler logic (just wires) and does not form combinational cycles. The conditions under which an EFork can be replaced by a USFork without any performance loss are formally derived. The last optimization avenue discussed in this dissertation is Elastic Bu er Controller (EBC) merging. In a typical synchronous elastic control network, some EBCs may activate their corresponding latches at similar schedules. This work provides a framework for fi nding and merging such controllers in any control network; including open networks (i.e., when the environment abstract is not available or required to be flexible) as well as networks incorporating variable latency units. Replacing EForks with USForks under some equivalence conditions as well as EBC merging have been fully automated in a tool, HGEN. The impact of this work will help achieve elasticity at a reduced cost. It will broaden the class of circuits that can be elasticized with acceptable overhead (circuits that designers would otherwise nd it too expensive to elasticize). In a MiniMIPS processor case study, comparing to a basic control network implementation, the optimization techniques of this dissertation accumulatively achieve reductions in the control network area, dynamic, and leakage power of 73.2%, 68.6%, and 69.1%, respectively

Compiling Irregular Software to Specialized Hardware

High-level synthesis (HLS) has simplified the design process for energy-efficient hardware accelerators: a designer specifies an accelerator’s behavior in a “high-level” language, and a toolchain synthesizes register-transfer level (RTL) code from this specification. Many HLS systems produce efficient hardware designs for regular algorithms (i.e., those with limited conditionals or regular memory access patterns), but most struggle with irregular algorithms that rely on dynamic, data-dependent memory access patterns (e.g., traversing pointer-based structures like lists, trees, or graphs). HLS tools typically provide imperative, side-effectful languages to the designer, which makes it difficult to correctly specify and optimize complex, memory-bound applications. In this dissertation, I present an alternative HLS methodology that leverages properties of functional languages to synthesize hardware for irregular algorithms. The main contribution is an optimizing compiler that translates pure functional programs into modular, parallel dataflow networks in hardware. I give an overview of this compiler, explain how its source and target together enable parallelism in the face of irregularity, and present two specific optimizations that further exploit this parallelism. Taken together, this dissertation verifies my thesis that pure functional programs exhibiting irregular memory access patterns can be compiled into specialized hardware and optimized for parallelism. This work extends the scope of modern HLS toolchains. By relying on properties of pure functional languages, our compiler can synthesize hardware from programs containing constructs that commercial HLS tools prohibit, e.g., recursive functions and dynamic memory allocation. Hardware designers may thus use our compiler in conjunction with existing HLS systems to accelerate a wider class of algorithms than before