Microprocessor energy characterization and optimization through fast, accurate, and flexible simulation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 99-102).Energy dissipation is emerging as a key constraint for both high-performance and embedded microprocessor designs, requiring computer architects to consider energy in addition to performance when evaluating design decisions. A major limitation is the general difficulty in analyzing the energy impact of architectural and microarchitectural features without constructing detailed implementations and running slow simulations. This thesis first describes the design of a fast, accurate, and flexible circuit simulation tool which enables transition-sensitive studies of microprocessor energy consumption that would otherwise be impossible or impractical. With a simulation infrastructure in place, various optimizations are implemented that target the entire datapath and cache energy consumption. The individual energy optimizations are analyzed in detail, and the microprocessor design is characterized using various energy breakdowns and studies of the bit correlation between data values. This work shows that a few relatively simple energy-saving techniques can have a large impact in the implementation of an energy-efficient microprocessor. By fully characterizing the energy usage, this thesis establishes a coherent vision of microprocessor energy consumption, and serves as a basis and motivation for further energy optimizations.by Ronny Krashinsky.S.M

Vector-thread architecture and implementation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 181-186).This thesis proposes vector-thread architectures as a performance-efficient solution for all-purpose computing. The VT architectural paradigm unifies the vector and multithreaded compute models. VT provides the programmer with a control processor and a vector of virtual processors. The control processor can use vector-fetch commands to broadcast instructions to all the VPs or each VP can use thread-fetches to direct its own control flow. A seamless intermixing of the vector and threaded control mechanisms allows a VT architecture to flexibly and compactly encode application parallelism and locality. VT architectures can efficiently exploit a wide variety of loop-level parallelism, including non-vectorizable loops with cross-iteration dependencies or internal control flow. The Scale VT architecture is an instantiation of the vector-thread paradigm designed for low-power and high-performance embedded systems. Scale includes a scalar RISC control processor and a four-lane vector-thread unit that can execute 16 operations per cycle and supports up to 128 simultaneously active virtual processor threads. Scale provides unit-stride and strided-segment vector loads and stores, and it implements cache refill/access decoupling. The Scale memory system includes a four-port, non-blocking, 32-way set-associative, 32 KB cache. A prototype Scale VT processor was implemented in 180 nm technology using an ASIC-style design flow. The chip has 7.1 million transistors and a core area of 16.6 mm2, and it runs at 260 MHz while consuming 0.4-1.1 W. This thesis evaluates Scale using a diverse selection of embedded benchmarks, including example kernels for image processing, audio processing, text and data processing, cryptography, network processing, and wireless communication.(cont.) Larger applications also include a JPEG image encoder and an IEEE 802.11 la wireless transmitter. Scale achieves high performance on a range of different types of codes, generally executing 3-11 compute operations per cycle. Unlike other architectures which improve performance at the expense of increased energy consumption, Scale is generally even more energy efficient than a scalar RISC processor.by Ronny Meir Krashinsky.Ph.D