Automatic Generation of Transducer Models for Bus-Based MPSoC Design

This paper presents methods for automatic generation of models of Transducer, a highly flexible communication module for interfacing Multiprocessor System-on-Chip (MPSoC) components. We describe the transducer architecture, comprising the bus interface, high-level communication controllers and buffer management blocks. The well-defined architecture of the transducer enables automatic generation of its Transaction-level and Register-transfer level (RTL) models. Moreover, the simple interface of the transducer provides for a well-defined software interface, making it easy to update the software after changes in MPSoC platform. Our experimental results show that MPSoC design for industrial-size applications, such as MP3 decoder and JPEG encoder, greatly benefits from automatic generation of transducer models. We found productivity gains of 9-23× due to significant savings in modeling effort. On the quality axis, we show that MPSoC communication design using automatically generated transducers has very little overhead in communication delay over a fully connected point-to-point communication architecture. Finally, we show that our automatically generated TLMs greatly reduce the system-level modeling time and provide a fast executable model for early functional validation

Pre-validation of SoC via hardware and software co-simulation

Abstract. System-on-chips (SoCs) are complex entities consisting of multiple hardware and software components. This complexity presents challenges in their design, verification, and validation. Traditional verification processes often test hardware models in isolation until late in the development cycle. As a result, cooperation between hardware and software development is also limited, slowing down bug detection and fixing. This thesis aims to develop, implement, and evaluate a co-simulation-based pre-validation methodology to address these challenges. The approach allows for the early integration of hardware and software, serving as a natural intermediate step between traditional hardware model verification and full system validation. The co-simulation employs a QEMU CPU emulator linked to a register-transfer level (RTL) hardware model. This setup enables the execution of software components, such as device drivers, on the target instruction set architecture (ISA) alongside cycle-accurate RTL hardware models. The thesis focuses on two primary applications of co-simulation. Firstly, it allows software unit tests to be run in conjunction with hardware models, facilitating early communication between device drivers, low-level software, and hardware components. Secondly, it offers an environment for using software in functional hardware verification. A significant advantage of this approach is the early detection of integration errors. Software unit tests can be executed at the IP block level with actual hardware models, a task previously only possible with costly system-level prototypes. This enables earlier collaboration between software and hardware development teams and smoothens the transition to traditional system-level validation techniques.Järjestelmäpiirin esivalidointi laitteiston ja ohjelmiston yhteissimulaatiolla. Tiivistelmä. Järjestelmäpiirit (SoC) ovat monimutkaisia kokonaisuuksia, jotka koostuvat useista laitteisto- ja ohjelmistokomponenteista. Tämä monimutkaisuus asettaa haasteita niiden suunnittelulle, varmennukselle ja validoinnille. Perinteiset varmennusprosessit testaavat usein laitteistomalleja eristyksissä kehityssyklin loppuvaiheeseen saakka. Tämän myötä myös yhteistyö laitteisto- ja ohjelmistokehityksen välillä on vähäistä, mikä hidastaa virheiden tunnistamista ja korjausta. Tämän diplomityön tavoitteena on kehittää, toteuttaa ja arvioida laitteisto-ohjelmisto-yhteissimulointiin perustuva esivalidointimenetelmä näiden haasteiden ratkaisemiseksi. Menetelmä mahdollistaa laitteiston ja ohjelmiston varhaisen integroinnin, toimien luonnollisena välietappina perinteisen laitteistomallin varmennuksen ja koko järjestelmän validoinnin välillä. Yhteissimulointi käyttää QEMU suoritinemulaattoria, joka on yhdistetty rekisterinsiirtotason (RTL) laitteistomalliin. Tämä mahdollistaa ohjelmistokomponenttien, kuten laiteajureiden, suorittamisen kohdejärjestelmän käskysarja-arkkitehtuurilla (ISA) yhdessä kellosyklitarkkojen RTL laitteistomallien kanssa. Työ keskittyy kahteen yhteissimulaation pääsovellukseen. Ensinnäkin se mahdollistaa ohjelmiston yksikkötestien suorittamisen laitteistomallien kanssa, varmistaen kommunikaation laiteajurien, matalan tason ohjelmiston ja laitteistokomponenttien välillä. Toiseksi se tarjoaa ympäristön ohjelmiston käyttämiseen toiminnallisessa laitteiston varmennuksessa. Merkittävä etu tästä lähestymistavasta on integraatiovirheiden varhainen havaitseminen. Ohjelmiston yksikkötestejä voidaan suorittaa jo IP-lohkon tasolla oikeilla laitteistomalleilla, mikä on aiemmin ollut mahdollista vain kalliilla järjestelmätason prototyypeillä. Tämä mahdollistaa aikaisemman ohjelmisto- ja laitteistokehitystiimien välisen yhteistyön ja helpottaa siirtymistä perinteisiin järjestelmätason validointimenetelmiin

Hardware Acceleration Using Functional Languages

Cílem této práce je prozkoumat možnosti využití funkcionálního paradigmatu pro hardwarovou akceleraci, konkrétně pro datově paralelní úlohy. Úroveň abstrakce tradičních jazyků pro popis hardwaru, jako VHDL a Verilog, přestáví stačit. Pro popis na algoritmické či behaviorální úrovni se rozmáhají jazyky původně navržené pro vývoj softwaru a modelování, jako C/C++, SystemC nebo MATLAB. Funkcionální jazyky se s těmi imperativními nemůžou měřit v rozšířenosti a oblíbenosti mezi programátory, přesto je předčí v mnoha vlastnostech, např. ve verifikovatelnosti, schopnosti zachytit inherentní paralelismus a v kompaktnosti kódu. Pro akceleraci datově paralelních výpočtů se často používají jednotky FPGA, grafické karty (GPU) a vícejádrové procesory. Praktická část této práce rozšiřuje existující knihovnu Accelerate pro počítání na grafických kartách o výstup do VHDL. Accelerate je možno chápat jako doménově specifický jazyk vestavěný do Haskellu s backendem pro prostředí NVIDIA CUDA. Rozšíření pro vysokoúrovňovou syntézu obvodů ve VHDL představené v této práci používá stejný jazyk a frontend.The aim of this thesis is to research how the functional paradigm can be used for hardware acceleration with an emphasis on data-parallel tasks. The level of abstraction of the traditional hardware description languages, such as VHDL or Verilog, is becoming to low. High-level languages from the domains of software development and modeling, such as C/C++, SystemC or MATLAB, are experiencing a boom for hardware description on the algorithmic or behavioral level. Functional Languages are not so commonly used, but they outperform imperative languages in verification, the ability to capture inherent paralellism and the compactness of code. Data-parallel task are often accelerated on FPGAs, GPUs and multicore processors. In this thesis, we use a library for general-purpose GPU programs called Accelerate and extend it to produce VHDL. Accelerate is a domain-specific language embedded into Haskell with a backend for the NVIDIA CUDA platform. We use the language and its frontend, and create a new backend for high-level synthesis of circuits in VHDL.

Modeling Power Consumption and Temperature in TLM Models

International audienceMany techniques and tools exist to estimate the power consumption and the temperature map of a chip. These tools help the hardware designers develop power efficient chips in the presence of temperature constraints. For this task, the application can be ignored or at least abstracted by some high level scenarios; at this stage, the actual embedded software is generally not available yet. However, after the hardware is defined, the embedded software can still have a significant influence on the power consumption; i.e., two implementations of the same application can consume more or less power. Moreover, the actual software powe

EARLY PERFORMANCE PREDICTION METHODOLOGY FOR MANY-CORES ON CHIP BASED APPLICATIONS

Modern high performance computing applications such as personal computing, gaming, numerical simulations require application-specific integrated circuits (ASICs) that comprises of many cores. Performance for these applications depends mainly on latency of interconnects which transfer data between cores that implement applications by distributing tasks. Time-to-market is a critical consideration while designing ASICs for these applications. Therefore, to reduce design cycle time, predicting system performance accurately at an early stage of design is essential. With process technology in nanometer era, physical phenomena such as crosstalk, reflection on the propagating signal have a direct impact on performance. Incorporating these effects provides a better performance estimate at an early stage. This work presents a methodology for better performance prediction at an early stage of design, achieved by mapping system specification to a circuit-level netlist description. At system-level, to simplify description and for efficient simulation, SystemVerilog descriptions are employed. For modeling system performance at this abstraction, queueing theory based bounded queue models are applied. At the circuit level, behavioral Input/Output Buffer Information Specification (IBIS) models can be used for analyzing effects of these physical phenomena on on-chip signal integrity and hence performance. For behavioral circuit-level performance simulation with IBIS models, a netlist must be described consisting of interacting cores and a communication link. Two new netlists, IBIS-ISS and IBIS-AMI-ISS are introduced for this purpose. The cores are represented by a macromodel automatically generated by a developed tool from IBIS models. The generated IBIS models are employed in the new netlists. Early performance prediction methodology maps a system specification to an instance of these netlists to provide a better performance estimate at an early stage of design. The methodology is scalable in nanometer process technology and can be reused in different designs

Optimierung der Energie und Power getriebenen Architekturexploration für Multicore und heterogenes System on Chip

The contribution of this work builds on top of the established virtual prototype platforms to improve both SoC design quality and productivity. Initially, an automatic system-level power estimation framework was developed to address the critical issue of early power estimation in SoC design. The estimation framework models the static and dynamic power consumption of the hardware components. These models are created from the normalized values of the basic design components of SoC, obtained through one-time power simulation of RTL hardware models. The framework allows dynamic technology node reconfiguration for power estimation models. Its instantaneous power reporting aids the detection of possible hotspot early into the design process. Adding this additional data in conjunction with a steadily growing design space of complex heterogeneous SoC, finding the right parameter configuration is a challenging and laborious task for a system-level designer. This work addresses this bottleneck by optimizing the design space exploration (DSE) process for MPSoC design. An automatic DSE framework for virtual platforms (VPs) was developed which is flexible and allows the selection optimal parameter configuration without pre-existing knowledge. To reduce exploration time, the framework is equipped with several multi-objective optimization techniques based on simulated annealing and a genetic algorithm. Lastly, to aid HW/SW partitioning at system-level, a flexible and automated workflow (SW2TLM) is presented. It allows the designer to explore various possible partitioning scenarios without going into depth of the hardware architecture complexity and software integration. The framework generates system-level hardware accelerators from corresponding functionality encoded in the software code and integrates them into the VP. Power consumption and time speedups of acceleration is reported to the designer, which further increases the quality and productivity of the development process towards the final architecture. The presented tools are evaluated using a state-of-the-art VP for a range of single and multi-core applications. Viewing the energy delay product, a reduction in exploration time was recorded at approximately 62% (worst case), maintaining optimal parameter accuracy of 90% compared to previous techniques. While the SW2TLM further increases the exploration versatility by combining modern high-level synthesis with system-level architectural exploration.Der Beitrag dieser Arbeit baut auf dem etablierten Konzept der virtuellen Prototyp (VP) Plattformen auf, um die Qualität und die Produktivität des Entwurfsprozesses zu verbessern. Zunächst wurde ein automatisches System-Level-Framework entwickelt, um Verlustleistungsabschätzung für SoC-Designs in einer deutlich früheren Entwicklungsphase zu ermöglichen. Hierfür werden statischen und dynamischen Energieverbrauchsanteile individueller Hardwareelemente durch ein abstraktes Modell ausgedrückt. Das Framework ermöglicht eine dynamische Anpassung des Technologieknotens sowie die Integration neuer Leistungsmodelle für Drittanbieterkomponenten. Die kontinuierliche Erfassung der Energieverbrauchseigenschaften und ihre grafische Darstellung Benutzeroberfläche unterstützt zusätzlich die frühzeitige Identifikation möglicher Hotspots. Durch die Bereitstellung zusätzlicher Daten, in Verbindung mit einem stetig wachsenden Entwurfsraum komplexer SoCs, ist die Identifikation der richtigen Parameterkonfiguration eine zeitintensive Aufgabe. Die vorgelegten Konzepte erlauben eine gesteigerte Automatisierung des Explorationsprozesses. Techniken der mehrdimensionalen Optimierung, basierend auf Simulated Annealing und genetischer Algorithmen erlauben die Identifikation von geeigneten Konfigurationen ohne vorheriges Wissen oder Erfahrungswerte Schließlich wurde zur Unterstützung der HW/SW -Partitionierung auf System-Ebene ein flexibler und automatisierter Workflow entwickelt. Er ermöglicht es dem Designer verschiedene mögliche Partitionierungsszenarien zu untersuchen, ohne sich in die Komplexität der Hardwarearchitektur und der Softwareintegration zu vertiefen. Das Framework erzeugt abstrakte Beschleunigermodelle aus entsprechenden Softwarefunktionen und integriert sie nahtlos in den ausführbare VP. Detaillierte Daten zum Energieverbrauch, Beschleunigungsfaktor und Kommunikationsoverhead der Partitionierung werden erfasst und dem Designer zur Verfügung gestellt, was die Qualität und Produktivität des weiter erhöht. Die vorgestellten Tools werden mit einer modernen VP für verschiedene SW-Anwendungen evaluiert. Bei Betrachtung des Energieverzögerungsprodukts wurde eine Verringerung der Explorationszeit um mehr als 62% bei 90% Parametergenauigkeit festgestell. Darauf aufbauend, erleichtert die automatisierte Untersuchung verschiedener HW/SW Partitionierungen die Entwicklung heterogener Architekturen durch die Kombination moderner HLS mit Architektur-Exploration auf der Systemebene

Achieving Accurate Predictions of Future Events Under Hardware Heterogeneity

Heterogeneous hardware is becoming increasingly available in modern hardware, while research breakthroughs enforce the expectation that heterogeneity will keep increasing in the future. Significant gains can be achieved via appropriate utilization of heterogeneity, in terms of performance and power consumption, however, poor utilization can have a detrimental effect. Intelligent scheduling and resource management is a crucial challenge we need to overcome in order to harvest the full potential of heterogeneous hardware. As systems become larger and include greater levels of hardware diversity, the importance of intelligent scheduling and resource management is further accentuated.This dissertation presents techniques that aid the process of scheduling and resource management in the presence of heterogeneous hardware, via accurately predicting upcoming runtime events. With a proactive and accurate view of the near future, schedulers can utilize the underlying hardware more efficiently, and fully take advantage of the available benefits.By adapting a majority element heuristic, this dissertation significantly improves the accuracy of predicting memory addresses about to be accessed, while reducing prediction-related costs by a factor of ten thousand compared to previously proposed predictive approaches. Coupled with novel microarchitectural modifications, accurate address predictions are shown to improve the performance of heterogeneous memory architectures.Machine learning-based performance predictors are further presented, capable of predicting a program's performance when executed on a given general-purpose core. Trained to model the subtleties of the interaction between hardware and software, these predictors are capable of generating highly accurate predictions even for cores with varied Instruction Set Architectures. Utilizing these performance predictions for job scheduling, is shown to improve overall system performance. The trained predictors are further examined and interpreted in order to visualize the correlations between features picked up and amplified during training.Finally, this dissertation demonstrates that scheduling algorithms cannot guarantee deriving an optimal schedule during realistic execution scenarios due to the underlying hardware heterogeneity, the wide range of runtime requirements of software, as well as prediction error from performance predictors. In response, deep neural networks are trained to select one scheduling approach from a list of options with varied overheads and correctness guarantees. The scheduling approach chosen, is the one which will most likely return the highest-performance schedule with the lowest overhead, given a particular instance of the job-to-core assignment problem