Power dissipation is now both a key constraint and an application driver in VLSI systems. For a specific application, the energy efficiency of different implementations can differ by multiple orders of magnitude. This work surveys a range of techniques available to improve energy efficiency and highlights their cumulative benefit. Understanding, adopting and adapting selected techniques from full-custom solutions can help bridge the efficiency gap for the ASIC designs. Architecture and micro-architecture choices yield multiple-order of magnitude improvements in power dissipation by matching the structure of the design to the structure of the application and by providing multiple operating and power-down modes. The combination of methodology and full-custom circuit techniques and libraries provide benefits primarily due to reduced parasitic loading enabling the improved performance to be translated into the potential for factor-of-3 to factor-of-10 improvements in power.

The Imagine stream processor is a 21 million transistor chip implemented by a collaboration between Stanford University and Texas Instruments in a 1.5 V 0.15 /spl mu/m process with five layers of aluminum metal. The VLSI design, clocking, and verification methodologies for the Imagine processor are presented. These methodologies enabled a small team of graduate students with limited resources to design a high-performance media processor in a modern ASIC flow.

Custom design, in which the designer controls the physical structure of the chip, can greatly improve the speed, power, and delay of an ASIC chip without affecting design time. Through floorplanning and tiling data paths, the designer places the critical wires first, before the logic is placed. Crafted datapath cells structure wiring at the other end of the spectrum by keeping local wires short enabling the use of minimum sized drivers. Routing the wires first gives early visibility of timing issues, allows the design to be optimized to drive the exact wire load, and enables the use of fast circuit styles.

Exceptions have traditionally been used to handle infrequently occurring and unpredictable events during normal program execution. Current trends in microprocessor and operating systems design continue to increase the cost of event handling. Because of the deep pipelines and wide out-of-order superscalar architectures of contemporary microprocessors, an event may need to nullify a large number of in-flight instructions. Large register files require existing software systems to save and restore a substantial amount of process state before executing an exception handler. At the same time, processors are executing in environments that supply higher event frequencies and demand higher performance. We have developed an alternative architecture, "concurrent event handling", that incorporates multithreading into event handling architectures. Instead of handling the event in the faulting thread's architectural and pipeline registers, the fault handler is forked into its own thread slot and executes concurrently with the faulting thread. Microbenchmark programs show a factor-of-3 speedup for concurrent event handling over a traditional architecture on code that takes frequent exceptions. We also demonstrate substantial speedups on two event-based applications. Concurrent event handling is implemented in the MIT's MAP (Multi-ALU Processor) chip.

Continuing reductions in on-chip geometries yield increasing numbers of transistors per chip and fundamentally faster devices but also result in effectively slower wires. This combination presents significant challenges for new microprocessor architectures. The disparity in performance between on-chip arithmetic units and memory creates longer effectively latencies. The changing balance between gate delay and wire delay penalizes global interactions. The MIT Multi-ALUP processor (IMRP) architecture incorporates three explicitly parallel mechanisms to address these challenges. Efficient intercluster interactions enable instruction scheduling across clustered arithmetic units. Deferred exceptions based on ERRVAL's facilitate aggressive instruction reordering and speculation. Zero-cycle multithreading provides latency tolerance without sacrificing single threaded performance. In this paper; we describe each of these mechanisms and quantify their impact on the area and routing of the cluster pipeline in the 5 Million transistor MAP chip. Zero-cycle multithreading accounts for over 44% of the total cluster area. Support for ERRVAL's requires very little area (less than 4%). The intercluster interaction mechanisms require minimal cluster area and less than 5% of the available global routing resources, but enable fully general access across clusters and between all arithmetic units.

Much of the improvement in computer performance over the last twenty years has come from faster transistors and architectural advances that increase parallelism. Historically, parallelism has been exploited either at the instruction level with a grain-size of a single instruction or by partitioning applications into coarse threads with grain-sizes of thousands of instructions. Fine-grain threads fill the parallelism gap between these extremes by enabling tasks with run lengths as small as 20 cycles. As this fine-grain parallelism is orthogonal to ILP and coarse threads, it complements both methods and provides an opportunity for greater speedup. This paper describes the efficient communication and synchronization mechanisms implemented in the Multi-ALU Processor (MAP) chip, including a thread creation instruction, register communication, and a hardware barrier. These register-based mechanisms provide 10 times faster communication and 60 times faster synchronization than mechanisms that operate via a shared on-chip cache. With a three-processor implementation of the MAP: fine-grain speedups of 1.2-2.1 are demonstrated on a suite of applications.

The M-Machine is an experimental multicomputer being developed to test architectural concepts motivated by the constraints of modern semiconductor technology and the demands of programming systems. The M-Machine computing nodes are connected with a 3-D mesh network; each node is a multithreaded processor incorporating 12 function units, on-chip cache, and local memory. The multiple function units are used to exploit both instruction-level and thread-level parallelism. A user accessible message passing system yields fast communication and synchronization between nodes. Rapid access to remote memory is provided transparently to the user with a combination of hardware and software mechanisms. This paper presents the architecture of the M-Machine and describes how its mechanisms attempt to maximize both single thread performance and overall system throughput. The architecture is complete and the MAP chip, which will serve as the M-Machine processing node, is currently being implemented.