37 research outputs found
Influence of Input/output Operations on Processor Performance
Nowadays, computers are frequently equipped with peripherals that transfer great
amounts of data between them and the system memory using direct memory access
techniques (i.e., digital cameras, high speed networks, . . . ). Those peripherals prevent the
processor from accessing system memory for significant periods of time (i.e., while they
are communicating with system memory in order to send or receive data blocks). In this
paper we study the negative effects that I/O operations from computer peripherals have on
processor performance. With the help of a set of routines (SMPL) used to make discrete
event simulators, we have developed a configurable software that simulates a computer
processor and main memory as well as the I/O scenarios where the periph-erals operate.
This software has been used to analyze the performance of four different processors in four
I/O scenarios: video capture, video capture and playback, high speed network, and serial
transmission
Visualization tool for computer architects
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (leaves 54-55).As computer architectures continue to grow in complexity, software developers and hardware engineers cope with the increasing complexity by developing proprietary applications, simulations and tool sets to understand the behavior of these complex systems. Although the field of information visualization is leading to powerful applications in many areas, information visualization applications for computer architecture development are either tightly coupled with a specific architecture or target a wide range of computer system data. This thesis introduces the Visualization Tool for Computer Architects (VISTA) Environment. The VISTA Environment is an extensible and modular information visualization environment for hardware engineers, software developers and educators to visualize data from a variety of computer architecture simulations at different levels of abstraction. The VISTA Environment leverages common attributes in simulation data, computer architecture visualizations, and computer architecture development methods to create a powerful information visualization environment to aid in designing, understanding and communicating complex computer architectures.by Aaron D. Mihalik.M.Eng
Maximizing resource utilization by slicing of superscalar architecture
Superscalar architectural techniques increase instruction throughput from one instruction per cycle to more than one instruction per cycle. Modern processors make use of several processing resources to achieve this kind of throughput. Control units perform various functions to minimize stalls and to ensure a continuous feed of instructions to execution units. It is vital to ensure that instructions ready for execution do not encounter a bottleneck in the execution stage; This thesis work proposes a dynamic scheme to increase efficiency of execution stage by a methodology called block slicing. Implementing this concept in a wide, superscalar pipelined architecture introduces minimal additional hardware and delay in the pipeline. The hardware required for the implementation of the proposed scheme is designed and assessed in terms of cost and delay. Performance measures of speed-up, throughput and efficiency have been evaluated for the resulting pipeline and analyzed
Hierarchical architecture design and simulation environment
The Hierarchical Architectural design and Simulation Environment (HASE)is
intended as a flexible tool for computer architects who wish to experiment with
alternative architectural configurations and design parameters. HASE is both
a design environment and a simulator. Architecture components are described
by a hierarchical library of objects defined in terms of an object oriented simulation language. HASE instantiates these objects to simulate and animate the
execution of a computer architecture. An event trace generated by the simulator
therefore describes the interaction between architecture components, for example,
fetch stages, address and data buses, sequencers, instruction buffers and register
files. The objects can model physical components at different abstraction levels,
eg. PMS (processor memory switch), ISP (instruction set processor) and RTL
(register transfer level). HASE applies the concepts of inheritance, encapsulation
and polymorphism associated with object orientation, to simplify the design and
implementation of an architecture simulation that models component operations
at different abstraction levels. For example, HASE can probe the performance
of a processor's floating point unit, executing a multiplication operation, at a
lower level of abstraction, i.e. the RTL, whilst simulating remaining architecture
components at a PMS level of abstraction. By adopting this approach, HASE
returns a more meaningful and relevant event trace from an architecture simulation. Furthermore, an animator visualises the simulation's event trace to clarify
the collaborations and interactions between architecture components. The prototype version of HASE is based on GSS (Graphical Support System), and DEMOS
(Discrete Event Modelling On Simula)
Methodology for designing simulators of computer architecture and organization
Π£ ΠΎΠ²ΠΎΠΌ ΡΠ°Π΄Ρ ΡΠ΅ ΡΠ°Π·ΠΌΠ°ΡΡΠ° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΡΠΊΠΈ ΠΏΡΠΈΡΡΡΠΏ Π΄ΠΈΠ·Π°ΡΠ½Ρ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΠΈΠ·
ΠΎΠ±Π»Π°ΡΡΠΈ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΠ΅ ΡΠ°ΡΡΠ½Π°ΡΠ° ΠΊΠΎΡΠΈ ΡΡΠ΅Π±Π° Π΄Π° ΠΎΠΌΠΎΠ³ΡΡΠΈ ΡΠ°Π·Π²ΠΎΡ
ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° Π΄ΠΈΠ³ΠΈΡΠ°Π»Π½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ° ΠΏΡΠΎΠΈΠ·Π²ΠΎΡΠ½ΠΎΠ³ Π½ΠΈΠ²ΠΎΠ° ΡΠ»ΠΎΠΆΠ΅Π½ΠΎΡΡΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΈΡ
Π·Π° ΡΠ°Π΄
Ρ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠΌ ΠΈ Π΄ΠΈΡΡΡΠΈΠ±ΡΠΈΡΠ°Π½ΠΎΠΌ ΠΎΠΊΡΡΠΆΠ΅ΡΡ. ΠΠ° Π±ΠΈ ΡΠ΅ ΠΎΠΌΠΎΠ³ΡΡΠΈΠΎ ΡΠΎΡΠΌΠΈΡΠ°ΡΠ΅
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ Π½Π° ΠΏΠΎΡΠ΅ΡΠΊΡ ΡΠ°Π΄Π° ΡΠ΅ ΠΏΡΠΈΠΊΠ°Π·Π°Π½ ΠΏΡΠ΅Π³Π»Π΅Π΄ Π½Π°ΡΡΠ°Π²Π΅ Ρ ΠΎΠ±Π»Π°ΡΡΠΈ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅
ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΠ΅ ΡΠ°ΡΡΠ½Π°ΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π½ΠΈΠΌ ΡΡΡΠ΄ΠΈΡΠ°ΠΌΠ°, ΠΊΠ°ΠΎ ΠΈ ΠΏΡΠ΅Π³Π»Π΅Π΄ ΠΎΠ±Π»Π°ΡΡΠΈ
ΠΏΡΠΎΡΠ΅ΠΊΡΠΎΠ²Π°ΡΠ° ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° Π³Π΄Π΅ ΡΠ΅ ΠΏΠΎΡΠ΅Π±Π°Π½ Π°ΠΊΡΠ΅Π½Π°Ρ Π±ΠΈΠΎ ΡΡΠ°Π²ΡΠ΅Π½ Π½Π° ΠΎΠ±Π»Π°ΡΡΠΈ
ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠ³ ΠΈ Π΄ΠΈΡΡΡΠΈΠ±ΡΠΈΡΠ°Π½ΠΎΠ³ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΈΡΠ°ΡΠ° ΠΊΠΎΡΠ΅ ΡΡΡΠ΄Π΅Π½ΡΠΈ ΡΡΠ΅Π±Π° Π΄Π° ΠΏΠΎΠ·Π½Π°ΡΡ ΠΊΠ°ΠΎ
Π±ΠΈ ΠΌΠΎΠ³Π»ΠΈ Π΄Π° ΡΠ°Π·Π²ΠΈΡΡ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ΅ ΠΊΠΎΡΠΈ ΠΎΠΌΠΎΠ³ΡΡΠ°Π²Π°ΡΡ ΡΠ°Π΄ Ρ ΡΠ°ΠΊΠ²ΠΎΠΌ ΠΎΠΊΡΡΠΆΠ΅ΡΡ. ΠΠ°
ΠΎΡΠ½ΠΎΠ²Ρ ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π΅ Π΅Π²Π°Π»ΡΠ°ΡΠΈΡΠ΅ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΠΊΠΎΡΠΈ ΡΠ΅ ΠΊΠΎΡΠΈΡΡΠ΅ Ρ Π½Π°ΡΡΠ°Π²ΠΈ ΠΈΠ· ΠΎΠ±Π»Π°ΡΡΠΈ
Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΠ΅ ΡΠ°ΡΡΠ½Π°ΡΠ° Π° ΠΊΠΎΡΠΈ ΠΈΠΌΠ°ΡΡ ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠΈΠ² ΠΈΠ·Π²ΠΎΡΠ½ΠΈ ΠΊΠΎΠ΄
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΡΠ΅ ΡΠ΅ΡΠ΅ΡΠ΅ ΠΊΠΎΡΠ΅ ΡΠ΅ Π·Π°ΡΠ½ΠΈΠ²Π° Π½Π° ΠΊΠΎΡΠΈΡΡΠ΅ΡΡ ΡΠ»ΠΎΡΠ΅Π²ΠΈΡΠ΅ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΊΠΎΠ΄
ΠΊΠΎΡΠ΅ ΡΠ΅ ΡΠ²Π°ΠΊΠΈ ΡΠ»ΠΎΡ ΠΎΠ΄Π³ΠΎΠ²ΠΎΡΠ°Π½ Π·Π° Π΄ΡΡΠ³ΠΈ Π²ΠΈΠ΄ ΠΎΠ±ΡΠ°Π΄Π΅ ΠΈ ΠΊΠΎΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΡΠ΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ
ΡΠ΅ΡΠ΅ΡΠ΅ ΡΠ΅ ΡΠ°ΡΡΠΎΡΠΈ ΠΈΠ· ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ° ΠΏΠ΅Ρ ΡΠ»ΠΎΡΠ΅Π²Π°: Π»ΠΎΠ³ΠΈΡΠΊΠΎΠ³, ΠΈΠ·Π²ΡΡΠ½ΠΎΠ³,
ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΠΎΠ½ΠΎΠ³, ΡΠΈΠΌΡΠ»Π°ΡΠΈΠΎΠ½ΠΎΠ³, ΠΈ ΡΠ»ΠΎΡΠ° ΡΠΈΠ·ΠΈΠΊΠ΅. ΠΠ΅ΡΠ°ΡΠΈ Π²Π΅Π·Π°Π½ΠΈ Π·Π° ΠΏΡΠΎΡΠ΅Π΄ΡΡΠ΅ ΠΈ
ΠΎΠ±ΡΠ°ΡΡΠ΅ΡΠ° ΡΠ΅Ρ
Π½ΠΈΠΊΠ° ΠΊΠΎΡΠ΅ ΡΠ΅ ΠΊΠΎΡΠΈΡΡΠ΅ Π·Π° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡΡ ΠΎΠ²ΠΈΡ
ΡΠ»ΠΎΡΠ΅Π²Π° ΡΡ ΠΏΡΠΈΠΊΠ°Π·Π°Π½ΠΈ Ρ
ΡΠ°Π΄Ρ. ΠΠ° ΡΠ²Π°ΠΊΠΈ ΡΠ»ΠΎΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠ³ ΡΠ΅ΡΠ΅ΡΠ° ΡΠ΅ Π΄Π°Ρ Π°Π½Π°Π»ΠΈΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» ΠΏΡΠΎΡΠ΅Π½Π΅
Π²ΡΠ΅ΠΌΠ΅Π½Π° ΠΈΠ·Π²ΡΡΠ°Π²Π°ΡΠ° ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ΅ Ρ Π·Π°Π²ΠΈΡΠ½ΠΎΡΡΠΈ ΠΎΠ΄ ΡΠ»Π°Π·Π½ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΠ°ΡΠ° ΠΏΡΠΈΠ»ΠΈΠΊΠΎΠΌ
ΡΠ°Π΄Π° Ρ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠΌ ΠΈ Π΄ΠΈΡΡΡΠΈΠ±ΡΠΈΡΠ°Π½ΠΎΠΌ ΠΎΠΊΡΡΠΆΠ΅ΡΡ. Π¦Π΅Π½ΡΡΠ°Π»Π½ΠΈ Π΄Π΅ΠΎ ΡΠ°Π΄Π° ΠΎΠΏΠΈΡΡΡΠ΅
ΡΠΈΠΌΡΠ»Π°ΡΠΎΡ Π΄ΠΈΡΠΊΡΠ΅ΡΠ½ΠΈΡ
Π΄ΠΎΠ³Π°ΡΠ°ΡΠ° ΠΎΠΏΡΡΠ΅ Π½Π°ΠΌΠ΅Π½Π΅ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ ΠΏΡΠ΅ΠΌΠ° ΠΎΠΏΠΈΡΠ°Π½ΠΎΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠΈ ΠΊΠ°ΠΎ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡΠ΅ ΡΠ°ΡΡΠ½Π°ΡΠ° ΠΊΠΎΡΠΈ ΡΠ΅
ΡΠΏΠΎΡΠΎΠ±Π°Π½ Π·Π° ΡΠ°Π΄ Ρ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠΌ ΠΈ Π΄ΠΈΡΡΡΠΈΠ±ΡΠΈΡΠ°Π½ΠΎΠΌ ΠΎΠΊΡΡΠΆΠ΅ΡΡ. ΠΠΏΠΈΡ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΠΈ
ΡΠ΅Π³ΠΎΠ²ΠΈΡ
Π΄Π΅Π»ΠΎΠ²Π° ΡΠ΅ Π΄Π°Ρ ΡΠ° ΡΡΠ°Π½ΠΎΠ²ΠΈΡΡΠ° Π΄Π΅ΡΠ°ΡΠ° ΠΈΠΌΠΏΠ»Π΅ΠΌΠ΅Π½ΡΠ°ΡΠΈΡΠ΅ Π³Π΄Π΅ ΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½ΠΈ
ΠΏΠ°ΠΊΠ΅ΡΠΈ ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅, ΠΊΠ°ΠΎ ΠΈ ΡΠ° ΡΡΠ°Π½ΠΎΠ²ΠΈΡΡΠ°
ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ° Π³Π΄Π΅ ΡΡ ΠΎΠΏΠΈΡΠ°Π½Π΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΡΠ½Π΅ ΡΠΈΡΡΠ°ΡΠΈΡΠ΅ Ρ ΠΊΠΎΡΠΈΠΌΠ° ΡΠ΅ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡ
ΠΌΠΎΠΆΠ΅ ΠΊΠΎΡΠΈΡΡΠΈΡΠΈ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ ΠΈΠΌΠΏΠ»Π΅ΠΌΠ΅Π½ΡΠ°ΡΠΈΡΠ΅ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΠΈ ΠΏΡΠ°ΡΠ΅ΡΠΈΡ
Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠ°
ΡΠ°Π·Π²ΠΈΡΠ΅Π½Π΅ ΡΡ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΡΡΠΊΠ΅ Π²Π΅ΠΆΠ±Π΅ ΠΈ ΠΏΡΠΎΡΠ΅ΠΊΡΠΈ ΠΈΠ· ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ° ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎ ΠΈ
Π΄ΠΈΡΡΡΠΈΠ±ΡΠΈΡΠ°Π½ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΈΡΠ°ΡΠ΅, ΠΊΠΎΡΠ΅ ΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π΅ Ρ Π½Π°ΡΡΠ°Π²ΠΊΡ ΡΠ°Π΄Π° ΠΊΠ°ΠΎ ΠΈ
Π΅Π²Π°Π»ΡΠ°ΡΠΈΡΠ° ΠΏΠΎΡΡΠΈΠ³Π½ΡΡΠΈΡ
ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠ° Ρ Π½Π°ΡΡΠ°Π²ΠΈ. ΠΠΎΡΠ΅Π΄ ΠΎΠ²Π΅ Π΅Π²Π°Π»ΡΠ°ΡΠΈΡΠ΅ Π½Π° ΠΊΡΠ°ΡΡ ΡΠ°Π΄Π° ΡΠ΅
ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΠΈ Π΅Π²Π°Π»ΡΠ°ΡΠΈΡΠ° ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΡΠ° ΡΡΠ°Π½ΠΎΠ²ΠΈΡΡΠ° Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»Π½ΠΈΡ
ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠ° ΠΈ ΡΠ° ΡΡΠ°Π½ΠΎΠ²ΠΈΡΡΠ° Π°Π½Π°Π»ΠΈΡΠΈΡΠΊΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π° ΠΊΠ°ΠΎ Π±ΠΈ ΡΠ΅ ΡΡΠ²ΡΠ΄ΠΈΠ»ΠΎ Ρ ΠΊΠΎΡΠΈΠΌ
ΡΠ»ΡΡΠ°ΡΠ΅Π²ΠΈΠΌΠ° ΠΈ Ρ ΠΊΠΎΠΌ ΠΎΠ±ΠΈΠΌΡ ΡΠ΅ ΠΌΠΎΠ³Ρ ΠΊΠΎΡΠΈΡΡΠΈΡΠΈ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠΈ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΈ ΡΡ
ΠΎΠ΄Π½ΠΎ
ΠΎΠΏΠΈΡΠ°Π½ΠΎΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠΈ..
Equivariant Symmetries for Inertial Navigation Systems
This paper investigates the problem of inertial navigation system (INS)
filter design through the lens of symmetry. The extended Kalman filter (EKF)
and its variants, have been the staple of INS filtering for 50 years; however,
recent advances in inertial navigation systems have exploited matrix Lie group
structure to design stochastic filters and state observers that have been shown
to display superior performance compared to classical solutions. In this work
we consider the case where a vehicle has an inertial measurement unit (IMU) and
a global navigation satellite system (GNSS) receiver. We show that all the
modern variants of the EKF for these sensors can be interpreted as the recently
proposed Equivariant Filter (EqF) design methodology applied to different
choices of symmetry group for the INS problem. This leads us to propose two new
symmetries for the INS problem that have not been considered in the prior
literature, and provide a discussion of the relative strengths and weaknesses
of all the different algorithms. We believe the collection of symmetries that
we present here capture all the sensible choices of symmetry for this problem
and sensor suite, and that the analysis provided is indicative of the relative
real-world performance potential of the different algorithms.Comment: Submitted to Automatic