BRISC-V: An Open-Source Architecture Design Space Exploration Toolbox

In this work, we introduce a platform for register-transfer level (RTL) architecture design space exploration. The platform is an open-source, parameterized, synthesizable set of RTL modules for designing RISC-V based single and multi-core architecture systems. The platform is designed with a high degree of modularity. It provides highly-parameterized, composable RTL modules for fast and accurate exploration of different RISC-V based core complexities, multi-level caching and memory organizations, system topologies, router architectures, and routing schemes. The platform can be used for both RTL simulation and FPGA based emulation. The hardware modules are implemented in synthesizable Verilog using no vendor-specific blocks. The platform includes a RISC-V compiler toolchain to assist in developing software for the cores, a web-based system configuration graphical user interface (GUI) and a web-based RISC-V assembly simulator. The platform supports a myriad of RISC-V architectures, ranging from a simple single cycle processor to a multi-core SoC with a complex memory hierarchy and a network-on-chip. The modules are designed to support incremental additions and modifications. The interfaces between components are particularly designed to allow parts of the processor such as whole cache modules, cores or individual pipeline stages, to be modified or replaced without impacting the rest of the system. The platform allows researchers to quickly instantiate complete working RISC-V multi-core systems with synthesizable RTL and make targeted modifications to fit their needs. The complete platform (including Verilog source code) can be downloaded at https://ascslab.org/research/briscv/explorer/explorer.html.Comment: In Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA '19

Near-Memory Address Translation

Memory and logic integration on the same chip is becoming increasingly cost effective, creating the opportunity to offload data-intensive functionality to processing units placed inside memory chips. The introduction of memory-side processing units (MPUs) into conventional systems faces virtual memory as the first big showstopper: without efficient hardware support for address translation MPUs have highly limited applicability. Unfortunately, conventional translation mechanisms fall short of providing fast translations as contemporary memories exceed the reach of TLBs, making expensive page walks common. In this paper, we are the first to show that the historically important flexibility to map any virtual page to any page frame is unnecessary in today's servers. We find that while limiting the associativity of the virtual-to-physical mapping incurs no penalty, it can break the translate-then-fetch serialization if combined with careful data placement in the MPU's memory, allowing for translation and data fetch to proceed independently and in parallel. We propose the Distributed Inverted Page Table (DIPTA), a near-memory structure in which the smallest memory partition keeps the translation information for its data share, ensuring that the translation completes together with the data fetch. DIPTA completely eliminates the performance overhead of translation, achieving speedups of up to 3.81x and 2.13x over conventional translation using 4KB and 1GB pages respectively.Comment: 15 pages, 9 figure

Application-aware Performance Optimization for Software Managed Manycore Architectures

abstract: One of the main goals of computer architecture design is to improve performance without much increase in the power consumption. It cannot be achieved by adding increasingly complex intelligent schemes in the hardware, since they will become increasingly less power-efficient. Therefore, parallelism comes up as the solution. In fact, the irrevocable trend of computer design in near future is still to keep increasing the number of cores while reducing the operating frequency. However, it is not easy to scale number of cores. One important challenge is that existing cores consume too much power. Another challenge is that cache-based memory hierarchy poses a serious limitation due to the rapidly increasing demand of area and power for coherence maintenance. In this dissertation, opportunities to resolve the aforementioned issues were explored in two aspects. Firstly, the possibility of removing hardware cache altogether, and replacing it with scratchpad memory with software management was explored. Scratchpad memory consumes much less power than caches. However, as data management logic is completely shifted to Software, how to reduce software overhead is challenging. This thesis presents techniques to manage scratchpad memory judiciously by exploiting application semantics and knowledge of data access patterns, thereby enabling optimization of data movement across the memory hierarchy. Experimental results show that the optimization was able to reduce stack data management overhead by 13X, produce better code mapping in more than 80% of the case, and improve performance by 83% in heap management. Secondly, the possibility of using software branch hinting to replace hardware branch prediction to completely eliminate power consumption on corresponding hardware components was explored. As branch predictor is removed from hardware, software logic is responsible for reducing branch penalty. Techniques to minimize the branch penalty by optimizing branch hint placement were proposed, which can reduce branch penalty by 35.4% over the state-of-the-art.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Simultaneous multithreading: Operating system perspective

Developing CPU architecture is a very complicated, iterative process that requires significant time and money investments. The motivation for this work is to find ways to decreases the amount of time and money needed for the development of hardware architectures. The main problem is that it is very difficult to determine the performance of the architecture, since it is impossible to take any performance measurements untill upon completion of the development process. Consecutively, it is impossible to improve the performance of the product or to predict the influence of different parts of the architecture on the architecture\u27s overall performance. Another problem is that this type of development does not allow for the developed system to be reconfigured or altered without complete re-development. . The solution to the problems mentioned above is the software simulators that allow researching the architecture before even starting to cut the silicon.. Simultaneous multithreading (SMT) is a modern approach to CPU design. This technique increases the system throughput by decreasing both total instruction delay and stall times of the CPU. The gain in performance of a typical SMT processor is achieved by allowing the instructions from several threads to be fetched by an operating system into the CPU simultaneously. In order to function successfully the CPU needs software support. In modern computer systems the influence of an operating system on overall system performance can no longer be ignored. It is important to understand that the union of the CPU and the supporting operating system and their interdependency determines the overall performance of any computer system. In the system that has been implemented on hardware level such analysis is impossible, since the hardware system is neither flexible nor configurable. However, in the SMT architecture, the system is capable of performing some useful work even if a task has generated an error. A wide range of simulators is described in the literature, and a lot of them are publicly accessible. The main goal of this work is to modify an existing SEVIOS/Topsy simulator to achieve a simple, configurable, publicly accessible SMT SEVIOS/Topsy simulator that must also include an SMT Topsy.. The simulator should demonstrate the fetching process of the SMT MIPS, as well as scheduling aspects of the CPU and the operating system integrated environment.. This work covers a broad range of aspects, among which are: 1) Completion of SMT MIPS and SMT Topsy specifications; 2) Integration of MXS into SIMOS/Topsy; 3) Modifications to the fetching unit of MXS that allow to support SMT; 4) Addition of SMT support to Topsy;; This work uses Topsy/R4000 simulator developed at Swiss Federal Institute of Technology, and the MXS (R10000) part of the SimOS simulator developed at Stanford University. Development process utilizes C high-level language, Intel and MIPS assembly languages. The result of this work is a development of a complete computer system software simulator. The simulator allows taking performance measurements and reconfiguration of SMT Topsy and the fetching unit of the SMT MXS. The simulator is modular: that is any of its parts can be substituted with other parts that perform similar functionality. It also means that the whole simulator can be integrated into a larger scale simulation project. The development of this simulator significantly decreases the amount of time and money needed for the development of hardware architectures and provides new ways in researching the influence of an operating system on the performance of the computer system as a whole

Multithreading Aware Hardware Prefetching for Chip Multiprocessors

To take advantage of the processing power in the Chip Multiprocessors design, applications must be divided into semi-independent processes that can run concur- rently on multiple cores within a system. Therefore, programmers must insert thread synchronization semantics (i.e. locks, barriers, and condition variables) to synchro- nize data access between processes. Indeed, threads spend long time waiting to acquire the lock of a critical section. In addition, a processor has to stall execution to wait for load data accesses to complete. Furthermore, there are often independent instructions which include load instructions beyond synchronization semantics that could be executed in parallel while a thread waits on the synchronization semantics. The conveniences of the cache memories come with some extra cost in Chip Multiprocessors. Cache Coherence mechanisms address the Memory Consistency problem. However, Cache Coherence adds considerable overhead to memory accesses. Having aggressive prefetcher on different cores of a Chip Multiprocessor can definitely lead to significant system performance degradation when running multi-threaded applications. This result of prefetch-demand interference when a prefetcher in one core ends up pulling shared data from a producing core before it has been written, the cache block will end up transitioning back and forth between the cores and result in useless prefetch, saturating the memory bandwidth and substantially increase the latency to critical shared data. We present a hardware prefetcher that enables large performance improvements from prefetching in Chip Multiprocessors by significantly reducing prefetch-demand interference. Furthermore, it will utilize the time that a thread spends waiting on syn- chronization semantics to run ahead of the critical section to speculate and prefetch independent load instruction data beyond the synchronization semantics

Investigation of a simultaneous multithreaded architecture

Many enhancements have been made to the traditional general purpose load-store computer architectures. Among the enhancements are memory hierarchy improvements, branch prediction, and multiple issue processors. A major problem that exists with current microprocessor design is the disparity in the much larger increase in speed of the CPU versus the moderate increase in speed accessing main memory. The simultaneous multithreaded architecture is an extension of the single-threaded architecture that helps hide the performance penalty created by long-latency instructions, branch mispredictions, and memory accesses. Simultaneous multithreaded architectures use a more flexible parallelism, which takes advantage of both instruction-level, and thread-level parallelism. The goal of this project was to design, simulate, and analyze a model of a simultaneous multithreaded architecture in order to evaluate design alternatives. The simulator was created by modifying a version of the Simple Scalar toolset, developed at the University of Wisconsin. The simulations provide documentation for an overall system performance improvement of a simulta neous multithreaded architecture. In early simulation results, performed with the same number of functional units, an improvement in the number of instructions per cycle (IPC) of between 43% and 58% was found using four threads versus a single thread. The horizontal waste rate, which measures the number of unused issue slots, was reduced between 35% and 46%. The vertical waste rate, which measures the percentage- of unused issue cycles (no issue slots used in a cycle), was reduced between 46% and 61%. These results are derived from a set of four sample programs. It was also found that increasing the number of certain functional units did not improve performance, whereas increasing the number of other types of functional units did have a significant positive impact on performance

A RECONFIGURABLE AND EXTENSIBLE EXPLORATION PLATFORM FOR FUTURE HETEROGENEOUS SYSTEMS

Accelerator-based -or heterogeneous- computing has become increasingly important in a variety of scenarios, ranging from High-Performance Computing (HPC) to embedded systems. While most solutions use sometimes custom-made components, most of today’s systems rely on commodity highend CPUs and/or GPU devices, which deliver adequate performance while ensuring programmability, productivity, and application portability. Unfortunately, pure general-purpose hardware is affected by inherently limited power-efficiency, that is, low GFLOPS-per-Watt, now considered as a primary metric. The many-core model and architectural customization can play here a key role, as they enable unprecedented levels of power-efficiency compared to CPUs/GPUs. However, such paradigms are still immature and deeper exploration is indispensable. This dissertation investigates customizability and proposes novel solutions for heterogeneous architectures, focusing on mechanisms related to coherence and network-on-chip (NoC). First, the work presents a non-coherent scratchpad memory with a configurable bank remapping system to reduce bank conflicts. The experimental results show the benefits of both using a customizable hardware bank remapping function and non-coherent memories for some types of algorithms. Next, we demonstrate how a distributed synchronization master better suits many-cores than standard centralized solutions. This solution, inspired by the directory-based coherence mechanism, supports concurrent synchronizations without relying on memory transactions. The results collected for different NoC sizes provided indications about the area overheads incurred by our solution and demonstrated the benefits of using a dedicated hardware synchronization support. Finally, this dissertation proposes an advanced coherence subsystem, based on the sparse directory approach, with a selective coherence maintenance system which allows coherence to be deactivated for blocks that do not require it. Experimental results show that the use of a hybrid coherent and non-coherent architectural mechanism along with an extended coherence protocol can enhance performance. The above results were all collected by means of a modular and customizable heterogeneous many-core system developed to support the exploration of power-efficient high-performance computing architectures. The system is based on a NoC and a customizable GPU-like accelerator core, as well as a reconfigurable coherence subsystem, ensuring application-specific configuration capabilities. All the explored solutions were evaluated on this real heterogeneous system, which comes along with the above methodological results as part of the contribution in this dissertation. In fact, as a key benefit, the experimental platform enables users to integrate novel hardware/software solutions on a full-system scale, whereas existing platforms do not always support a comprehensive heterogeneous architecture exploration

Towards easy and efficient processing of ultra-high resolution brain images

Ultra-high resolution 3D brain imaging is of great importance to the field of neuroscience as it provides a deep insight into brain anatomy and function. Such images may range between a few 100 gigabytes to terabytes in size and do not typically fit into computer memory. Lack of accessibility to the processing of these images is a threat to open science. This thesis aims to design a web system that will handle the storage and processing of ultra-high resolution neuroimaging data. The system architecture uses technologies such as Hadoop Distributed File System and Apache Spark. For the seamless integration neuroimaging pipelines into our system, we adopted NIfTI as our distributed data format and require that all neuroimaging pipelines be described in common formats such as Boutiques or BIDS. The large images are split into chunks, and also, recreated from the chunks. The effects of 2D slices and 3D blocks are investigated. Different algorithms to minimize number of seeks were designed and implemented. Results indicate that clustered reading of blocks achieves a significant reduction in processing time, and partitioning data into slices is most effective. The scalability of processing large images with Spark using a simple non-containerized and containerized pipeline was investigated. It was found that processing time of both algorithms scale well. As data may need to be written to and read from disk for containerized pipeline processing, the speedup provided by Spark's in-memory computing was also investigated. In-memory computing was found to provide significant speedup, however, this speedup may be less significant in more compute-intensive pipelines

Design of testbed and emulation tools

The research summarized was concerned with the design of testbed and emulation tools suitable to assist in projecting, with reasonable accuracy, the expected performance of highly concurrent computing systems on large, complete applications. Such testbed and emulation tools are intended for the eventual use of those exploring new concurrent system architectures and organizations, either as users or as designers of such systems. While a range of alternatives was considered, a software based set of hierarchical tools was chosen to provide maximum flexibility, to ease in moving to new computers as technology improves and to take advantage of the inherent reliability and availability of commercially available computing systems