Process technology scaling and hardware architecture specialization have vastly increased the need for chip design space exploration, while optimizing for power, performance, and area. Hammer is an open-source, reusable physical design (PD) flow generator that reduces design effort and increases portability by enforcing a separation among design-, tool-, and process technology-specific concerns with a modular software architecture. In this work, we outline Hammer's structure and highlight recent extensions that support both physical chip designers and hardware architects evaluating the merit and feasibility of their proposed designs. This is accomplished through the integration of more tools and process technologies---some open-source---and the designer-driven development of flow step generators. An evaluation of chip designs in process technologies ranging from 130nm down to 12nm across a series of RISC-V-based chips shows how Hammer-generated flows are reusable and enable efficient optimization for diverse applications.

DNN accelerators are often developed and evaluated in isolation without considering the cross-stack, system-level effects in real-world environments. This makes it difficult to appreciate the impact of Systemon-Chip (SoC) resource contention, OS overheads, and programming-stack inefficiencies on overall performance/energy-efficiency. To address this challenge, we present Gemmini, an open-source, full-stack DNN accelerator generator. Gemmini generates a wide design-space of efficient ASIC accelerators from a flexible architectural template, together with flexible programming stacks and full SoCs with shared resources that capture system-level effects. Gemmini-generated accelerators have also been fabricated, delivering up to three orders-of-magnitude speedups over high-performance CPUs on various DNN benchmarks.

We present a bang-bang phase-locked loop (PLL) generator that encapsulates design methodologies for its circuit blocks and the complete PLL system. The generator is fully automated and parameterized, producing the layout and schematic based on process characterization and top-level specifications. Three 14GHz PLLs are instantiated in TSMC 16nm, GF 14nm and Intel 22nm technologies, demonstrating the process portability. The rapid generation time of less than four days enables fast PLL design and technology porting. The PLL design fabricated in TSMC 16nm shows RMS jitter of 565.4fs and power of 6.64mW from a 0.9V supply.

Continued improvement in computing efficiency requires functional specialization of hardware designs. We present an agile design flow for custom SoCs using the Chipyard framework, an integrated SoC research and implementation environment for custom systems. Chipyard includes configurable, composable, open-source, generator-based designs that can be used across multiple stages of the hardware development flow while maintaining design intent and integration consistency. Through cloud FPGA simulation and rapid ASIC implementation, we demonstrate an iterative agile hardware design cycle which enables continuous validation of physically-realizable customized systems.

This work demonstrates a dual-core RISC-V system-on-chip (SoC) with integrated fine-grain power management. The 28-nm fully depleted silicon-on-insulator (FD-SOI) SoC integrates switched-capacitor voltage converters and 4-Gb/s off-chip serial links. The SoC runs applications with operating system support on dual RISC-V Rocket cores with vector accelerators. Runtime monitoring of microarchitectural counters allows prediction of future compute intensity, enabling the voltage state of the managed core to be adjusted quickly to optimize energy efficiency without sacrificing overall performance.

We present FireSim, an open-source simulation platform that enables cycle-exact microarchitectural simulation of large scale-out clusters by combining FPGA-accelerated simulation of silicon-proven RTL designs with a scalable, distributed network simulation. Unlike prior FPGA-accelerated simulation tools, FireSim runs on Amazon EC2 F1, a public cloud FPGA platform, which greatly improves usability, provides elasticity, and lowers the cost of large-scale FPGA-based experiments. We describe the design and implementation of FireSim and show how it can provide sufficient performance to run modern applications at scale, to enable true hardware-software co-design. As an example, we demonstrate automatically generating and deploying a target cluster of 1,024 3.2 GHz quad-core server nodes, each with 16 GB of DRAM, interconnected by a 200 Gbit/s network with 2 microsecond latency, which simulates at a 3.4 MHz processor clock rate (less than 1,000x slowdown over real-time). In aggregate, this FireSim instantiation simulates 4,096 cores and 16 TB of memory, runs ~14 billion instructions per second, and harnesses 12.8 million dollars worth of FPGAs—at a total cost of only ~$100 per simulation hour to the user. We present several examples to show how FireSim can be used to explore various research directions in warehouse-scale machine design, including modeling networks with high-bandwidth and low-latency, integrating arbitrary RTL designs for a variety of commodity and specialized datacenter nodes, and modeling a variety of datacenter organizations, as well as reusing the scale-out FireSim infrastructure to enable fast, massively parallel cycle-exact single-node microarchitectural experimentation.

Enabled by modern languages and retargetable compilers, software development is in a virtual “Cambrian explosion” driven by a critical mass of powerfully parameterized libraries; but hardware development practices lag far behind. We hypothesize that existing hardware construction languages (HCLs) and novel hardware compiler frameworks (HCFs) can put hardware development on a similar evolutionary path by enabling new hardware libraries to be independent of underlying process technologies including FPGA mappings. We support this claim by (1) evaluating the degree with which Chisel, an existing HCL, can support powerfully parameterized libraries, and (2) introducing the concept and implementation of an HCF that uses an open-source hardware intermediate representation, FIRRTL (Flexible Intermediate Representation for RTL), to transform target-independent RTL into technology-specific RTL. Finally, we evaluate many hardware compiler transformations, including simplifying transformations, analyses, optimizations, instrumentations, and specializations, which demonstrate the power of a combined HCL and HCF approach.