Piranha: a Scalable Architecture Based on Single-Chip Multiprocessing
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Implicitly-Multithreaded Processors
Appears in the Proceedings of the 30th Annual International Symposium on Computer Architecture (ISCA) Implicitly-Multithreaded Processors Il Park, Babak Falsafi∗ and T. N. Vijaykumar School of Electrical & Computer Engineering ∗Computer Architecture Laboratory (CALCM) Purdue University Carnegie Mellon University {parki,vijay}@ecn.purdue.edu [email protected] http://www.ece.cmu.edu/~impetus Abstract In this paper, we propose the Implicitly-Multi- Threaded (IMT) processor. IMT executes compiler-speci- This paper proposes the Implicitly-MultiThreaded fied speculative threads from a sequential program on a (IMT) architecture to execute compiler-specified specula- wide-issue SMT pipeline. IMT is based on the fundamental tive threads on to a modified Simultaneous Multithreading observation that Multiscalar’s execution model — i.e., pipeline. IMT reduces hardware complexity by relying on compiler-specified speculative threads [10] — can be the compiler to select suitable thread spawning points and decoupled from the processor organization — i.e., distrib- orchestrate inter-thread register communication. To uted processing cores. Multiscalar [10] employs sophisti- enhance IMT’s effectiveness, this paper proposes three cated specialized hardware, the register ring and address novel microarchitectural mechanisms: (1) resource- and resolution buffer, which are strongly coupled to the distrib- dependence-based fetch policy to fetch and execute suit- uted core organization. In contrast, IMT proposes to map able instructions, (2) context multiplexing to improve utili- speculative threads on to generic SMT. zation and map as many threads to a single context as IMT differs fundamentally from prior proposals, TME allowed by availability of resources, and (3) early thread- and DMT, for speculative threading on SMT. While TME invocation to hide thread start-up overhead by overlapping executes multiple threads only in the uncommon case of one thread’s invocation with other threads’ execution. -
Kaisen Lin and Michael Conley
Kaisen Lin and Michael Conley Simultaneous Multithreading ◦ Instructions from multiple threads run simultaneously on superscalar processor ◦ More instruction fetching and register state ◦ Commercialized! DEC Alpha 21464 [Dean Tullsen et al] Intel Hyperthreading (Xeon, P4, Atom, Core i7) Web applications ◦ Web, DB, file server ◦ Throughput over latency ◦ Service many users ◦ Slight delay acceptable 404 not Idea? ◦ More functional units and caches ◦ Not just storage state Instruction fetch ◦ Branch prediction and alignment Similar problems to the trace cache ◦ Large programs: inefficient I$ use Issue and retirement ◦ Complicated OOE logic not scalable Need more wires, hardware, ports Execution ◦ Register file and forwarding logic Power-hungry Replace complicated OOE with more processors ◦ Each with own L1 cache Use communication crossbar for a shared L2 cache ◦ Communication still fast, same chip Size details in paper ◦ 6-SS about the same as 4x2-MP ◦ Simpler CPU overall! SimOS: Simulate hardware env ◦ Can run commercial operating systems on multiple CPUs ◦ IRIX 5.3 tuned for multi-CPU Applications ◦ 4 integer, 4 floating-point, 1 multiprog PARALLELLIZED! Which one is better? ◦ Misses per completed instruction ◦ In general hard to tell what happens Which one is better? ◦ 6-SS isn’t taking advantage! Actual speedup metrics ◦ MP beats the pants off SS some times ◦ Doesn’t perform so much worse other times 6-SS better than 4x2-MP ◦ Non-parallelizable applications ◦ Fine-grained parallel applications 6-SS worse than 4x2-MP -
The Intro to GPGPU CPU Vs
12/12/11! The Intro to GPGPU . Dr. Chokchai (Box) Leangsuksun, PhD! Louisiana Tech University. Ruston, LA! ! CPU vs. GPU • CPU – Fast caches – Branching adaptability – High performance • GPU – Multiple ALUs – Fast onboard memory – High throughput on parallel tasks • Executes program on each fragment/vertex • CPUs are great for task parallelism • GPUs are great for data parallelism Supercomputing 20082 Education Program 1! 12/12/11! CPU vs. GPU - Hardware • More transistors devoted to data processing CUDA programming guide 3.1 3 CPU vs. GPU – Computation Power CUDA programming guide 3.1! 2! 12/12/11! CPU vs. GPU – Memory Bandwidth CUDA programming guide 3.1! What is GPGPU ? • General Purpose computation using GPU in applications other than 3D graphics – GPU accelerates critical path of application • Data parallel algorithms leverage GPU attributes – Large data arrays, streaming throughput – Fine-grain SIMD parallelism – Low-latency floating point (FP) computation © David Kirk/NVIDIA and Wen-mei W. Hwu, 2007! ECE 498AL, University of Illinois, Urbana-Champaign! 3! 12/12/11! Why is GPGPU? • Large number of cores – – 100-1000 cores in a single card • Low cost – less than $100-$1500 • Green computing – Low power consumption – 135 watts/card – 135 w vs 30000 w (300 watts * 100) • 1 card can perform > 100 desktops 12/14/09!– $750 vs 50000 ($500 * 100) 7 Two major players 4! 12/12/11! Parallel Computing on a GPU • NVIDIA GPU Computing Architecture – Via a HW device interface – In laptops, desktops, workstations, servers • Tesla T10 1070 from 1-4 TFLOPS • AMD/ATI 5970 x2 3200 cores • NVIDIA Tegra is an all-in-one (system-on-a-chip) ATI 4850! processor architecture derived from the ARM family • GPU parallelism is better than Moore’s law, more doubling every year • GPGPU is a GPU that allows user to process both graphics and non-graphics applications. -
A Speculative Control Scheme for an Energy-Efficient Banked Register File
IEEE TRANSACTIONS ON COMPUTERS, VOL. 54, NO. 6, JUNE 2005 741 A Speculative Control Scheme for an Energy-Efficient Banked Register File Jessica H. Tseng, Student Member, IEEE, and Krste Asanovicc, Member, IEEE Abstract—Multiported register files are critical components of modern superscalar and simultaneously multithreaded (SMT) processors, but conventional designs consume considerable die area and power as register counts and issue widths grow. Banked multiported register files consisting of multiple interleaved banks of lesser ported cells can be used to reduce area, power, and access time and previous work has shown that such designs can provide sufficient bandwidth for a superscalar machine. These previous banked designs, however, have complex control structures to avoid bank conflicts or to buffer conflicting requests, which add to design complexity and would likely limit cycle time. This paper presents a much simpler and faster control scheme that speculatively issues potentially conflicting instructions, then quickly repairs the pipeline if conflicts occur. We show that, once optimizations to avoid regfile reads are employed, the remaining read accesses observed in detailed simulations are close to randomly distributed and this contributes to the effectiveness of our speculative control scheme. For a four-issue superscalar processor with 64 physical registers, we show that we can reduce area by a factor of three, access time by 25 percent, and energy by 40 percent, while decreasing IPC by less than 5 percent. For an eight-issue SMT processor with 512 physical registers, area is reduced by a factor of seven, access time by 30 percent, and energy by 60 percent, while decreasing IPC by less than 2 percent. -
The Microarchitecture of a Low Power Register File
The Microarchitecture of a Low Power Register File Nam Sung Kim and Trevor Mudge Advanced Computer Architecture Lab The University of Michigan 1301 Beal Ave., Ann Arbor, MI 48109-2122 {kimns, tnm}@eecs.umich.edu ABSTRACT Alpha 21464, the 512-entry 16-read and 8-write (16-r/8-w) ports register file consumed more power and was larger than The access time, energy and area of the register file are often the 64 KB primary caches. To reduce the cycle time impact, it critical to overall performance in wide-issue microprocessors, was implemented as two 8-r/8-w split register files [9], see because these terms grow superlinearly with the number of read Figure 1. Figure 1-(a) shows the 16-r/8-w file implemented and write ports that are required to support wide-issue. This paper directly as a monolithic structure. Figure 1-(b) shows it presents two techniques to reduce the number of ports of a register implemented as the two 8-r/8-w register files. The monolithic file intended for a wide-issue microprocessor without hardly any register file design is slow because each memory cell in the impact on IPC. Our results show that it is possible to replace a register file has to drive a large number of bit-lines. In register file with 16 read and 8 write ports, intended for an eight- contrast, the split register file is fast, but duplicates the issue processor, with a register file with just 8 read and 8 write contents of the register file in two memory arrays, resulting in ports so that the impact on IPC is a few percent. -
System-On-A-Chip (Soc) & ARM Architecture
System-on-a-Chip (SoC) & ARM Architecture EE2222 Computer Interfacing and Microprocessors Partially based on System-on-Chip Design by Hao Zheng 2020 EE2222 1 Overview • A system-on-a-chip (SoC): • a computing system on a single silicon substrate that integrates both hardware and software. • Hardware packages all necessary electronics for a particular application. • which implemented by SW running on HW. • Aim for low power and low cost. • Also more reliable than multi-component systems. 2020 EE2222 2 Driven by semiconductor advances 2020 EE2222 3 Basic SoC Model 2020 EE2222 4 2020 EE2222 5 SoC vs Processors System on a chip Processors on a chip processor multiple, simple, heterogeneous few, complex, homogeneous cache one level, small 2-3 levels, extensive memory embedded, on chip very large, off chip functionality special purpose general purpose interconnect wide, high bandwidth often through cache power, cost both low both high operation largely stand-alone need other chips 2020 EE2222 6 Embedded Systems • 98% processors sold annually are used in embedded applications. 2020 EE2222 7 Embedded Systems: Design Challenges • Power/energy efficient: • mobile & battery powered • Highly reliable: • Extreme environment (e.g. temperature) • Real-time operations: • predictable performance • Highly complex • A modern automobile with 55 electronic control units • Tightly coupled Software & Hardware • Rapid development at low price 2020 EE2222 8 EECS222A: SoC Description and Modeling Lecture 1 Design Complexity Challenge Design• Productivity Complexity -
Alphaserver GS1280 Overview
QuickSpecs HP AlphaServer GS1280 Systems Overview HP AlphaServer GS1280 Models 8 and 16 1. Cable/DSL HUB 2. PCI/PCI-X I/O Expansion Drawer (optional) 3. PCI/PCI-X I/O Master Drawer (mandatory option) 4. System Building Block Drawer (Model 8 Includes 1 drawer, Model 16 includes 2 drawers) 5. 48-volt DC Power shelves, 3 power supplies per shelf (Model 8 includes 1 shelf, Model 16 includes 2 shelves) 6. AC input controller(s) (mandatory option) DA - 11921 Worldwide — Version 24 — July 23, 2007 Page 1 QuickSpecs HP AlphaServer GS1280 Systems Overview HP AlphaServer GS1280 Model 32 1. Cable/DSL HUB 2. I/O Expansion Drawer (optional) 3. I/O Master Drawer (mandatory option) 4. System Building Block Drawer (Model 32 includes four drawers) 5. Power supply, dual AC input is standard 6. AC input controllers (two mandatory options for Model 32) DA - 11921 Worldwide — Version 24 — July 23, 2007 Page 2 QuickSpecs HP AlphaServer GS1280 Systems Overview HP AlphaServer GS1280 Model 64 1. Cable/DSL HUB 2. I/O Expansion Drawer (optional) 3. I/O Master Drawer (one drawer is optional) 4. System Building Block Drawer (Model 64 includes eight drawers) 5. Power supply, dual AC input is standard (two included for Model 64) 6. AC input controllers (two mandatory options for Model 64) DA - 11921 Worldwide — Version 24 — July 23, 2007 Page 3 QuickSpecs HP AlphaServer GS1280 Systems Overview At A Glance AlphaServer GS1280 Systems Up to 64 Alpha 21364 EV7 processors at 1300 MHz and 1150 MHz with advanced on-chip memory controllers and switch logic capable of providing -
REPORT Compaq Chooses SMT for Alpha Simultaneous Multithreading
VOLUME 13, NUMBER 16 DECEMBER 6, 1999 MICROPROCESSOR REPORT THE INSIDERS’ GUIDE TO MICROPROCESSOR HARDWARE Compaq Chooses SMT for Alpha Simultaneous Multithreading Exploits Instruction- and Thread-Level Parallelism by Keith Diefendorff Given a full complement of on-chip memory, increas- ing the clock frequency will increase the performance of the As it climbs rapidly past the 100-million- core. One way to increase frequency is to deepen the pipeline. transistor-per-chip mark, the micro- But with pipelines already reaching upwards of 12–14 stages, processor industry is struggling with the mounting inefficiencies may close this avenue, limiting future question of how to get proportionally more performance out frequency improvements to those that can be attained from of these new transistors. Speaking at the recent Microproces- semiconductor-circuit speedup. Unfortunately this speedup, sor Forum, Joel Emer, a Principal Member of the Technical roughly 20% per year, is well below that required to attain the Staff in Compaq’s Alpha Development Group, described his historical 60% per year performance increase. To prevent company’s approach: simultaneous multithreading, or SMT. bursting this bubble, the only real alternative left is to exploit Emer’s interest in SMT was inspired by the work of more and more parallelism. Dean Tullsen, who described the technique in 1995 while at Indeed, the pursuit of parallelism occupies the energy the University of Washington. Since that time, Emer has of many processor architects today. There are basically two been studying SMT along with other researchers at Washing- theories: one is that instruction-level parallelism (ILP) is ton. Once convinced of its value, he began evangelizing SMT abundant and remains a viable resource waiting to be tapped; within Compaq. -
Comparative Study of Various Systems on Chips Embedded in Mobile Devices
Innovative Systems Design and Engineering www.iiste.org ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online) Vol.4, No.7, 2013 - National Conference on Emerging Trends in Electrical, Instrumentation & Communication Engineering Comparative Study of Various Systems on Chips Embedded in Mobile Devices Deepti Bansal(Assistant Professor) BVCOE, New Delhi Tel N: +919711341624 Email: [email protected] ABSTRACT Systems-on-chips (SoCs) are the latest incarnation of very large scale integration (VLSI) technology. A single integrated circuit can contain over 100 million transistors. Harnessing all this computing power requires designers to move beyond logic design into computer architecture, meet real-time deadlines, ensure low-power operation, and so on. These opportunities and challenges make SoC design an important field of research. So in the paper we will try to focus on the various aspects of SOC and the applications offered by it. Also the different parameters to be checked for functional verification like integration and complexity are described in brief. We will focus mainly on the applications of system on chip in mobile devices and then we will compare various mobile vendors in terms of different parameters like cost, memory, features, weight, and battery life, audio and video applications. A brief discussion on the upcoming technologies in SoC used in smart phones as announced by Intel, Microsoft, Texas etc. is also taken up. Keywords: System on Chip, Core Frame Architecture, Arm Processors, Smartphone. 1. Introduction: What Is SoC? We first need to define system-on-chip (SoC). A SoC is a complex integrated circuit that implements most or all of the functions of a complete electronic system. -
System-On-Chip Design with Virtual Components
past designs can a huge chip be com- pleted within a reasonable time. This FEATURE solution usually entails reusing designs from previous generations of products ARTICLE and often leverages design work done by other groups in the same company. Various forms of intercompany cross licensing and technology sharing Thomas Anderson can provide access to design technol- ogy that may be reused in new ways. Many large companies have estab- lished central organizations to pro- mote design reuse and sharing, and to System-on-Chip Design look for external IP sources. One challenge faced by IP acquisi- tion teams is that many designs aren’t well suited for reuse. Designing with with Virtual Components reuse in mind requires extra time and effort, and often more logic as well— requirements likely to be at odds with the time-to-market goals of a product design team. Therefore, a merchant semiconduc- tor IP industry has arisen to provide designs that were developed specifically for reuse in a wide range of applications. These designs are backed by documen- esign reuse for tation and support similar to that d semiconductor provided by a semiconductor supplier. Here in the Recycling projects has evolved The terms “virtual component” from an interesting con- and “core” commonly denote reusable Age, designing for cept to a requirement. Today’s huge semiconductor IP that is offered for system-on-a-chip (SOC) designs rou- license as a product. The latter term is reuse may sound like tinely require millions of transistors. promoted extensively by the Virtual Silicon geometry continues to shrink Socket Interface (VSI) Alliance, a joint a great idea. -
Lecture Notes
Lecture #4-5: Computer Hardware (Overview and CPUs) CS106E Spring 2018, Young In these lectures, we begin our three-lecture exploration of Computer Hardware. We start by looking at the different types of computer components and how they interact during basic computer operations. Next, we focus specifically on the CPU (Central Processing Unit). We take a look at the Machine Language of the CPU and discover it’s really quite primitive. We explore how Compilers and Interpreters allow us to go from the High-Level Languages we are used to programming to the Low-Level machine language actually used by the CPU. Most modern CPUs are multicore. We take a look at when multicore provides big advantages and when it doesn’t. We also take a short look at Graphics Processing Units (GPUs) and what they might be used for. We end by taking a look at Reduced Instruction Set Computing (RISC) and Complex Instruction Set Computing (CISC). Stanford President John Hennessy won the Turing Award (Computer Science’s equivalent of the Nobel Prize) for his work on RISC computing. Hardware and Software: Hardware refers to the physical components of a computer. Software refers to the programs or instructions that run on the physical computer. - We can entirely change the software on a computer, without changing the hardware and it will transform how the computer works. I can take an Apple MacBook for example, remove the Apple Software and install Microsoft Windows, and I now have a Window’s computer. - In the next two lectures we will focus entirely on Hardware. -
EE Concentration: System-On-A-Chip (Soc)
EE Concentration: System-on-a-Chip (SoC) Requirements: Complete ESE350, ESE370, CIS371, ESE532 Requirement Flow: Impact: The chip at the heart of your smartphone, tablet, or mp3 player (including the Apple A11, A12) is an SoC. The chips that run almost all of your gadgets today are SoCs. These are the current culmination of miniaturization and part count reduction that allows such systems to built inexpensively and from small part counts. These chips democratize innovation, by providing a platform for the deployment of novel ideas without requiring hundreds of millions of dollars to build new custom ICs. Description: Modern computational and control chips contain billions of transistors and run software that has millions of lines of code. They integrate complete systems including multiple, potentially heterogeneous, processing elements, sophisticated memory hierarchies, communications, and rich interfaces for inputs and outputs including sensing and actuations. To design these systems, engineers must understand IC technology, digital circuits, processor and accelerator architectures, networking, and composition and interfacing and be able to manage hardware/software trade-offs. This concentration prepares students both to participate in the design of these SoC architectures and to use SoC architectures as implementation vehicles for novel embedded computing tasks. Sample industries and companies: ● Integrated Circuit Design: ARM, IBM, Intel, Nvidia, Samsung, Qualcomm, Xilinx ● Consumer Electronics: Apple, Samsung, NEST, Hewlett Packard ● Systems: Amazon, CISCO, Google, Facebook, Microsoft ● Automotive and Aerospace: Boeing, Ford, Space-X, Tesla, Waymo ● Your startup Sample Job Titles: ● Hardware Engineer, Chip Designer, Chip Architect, Architect, Verification Engineer, Software Engineering, Embedded Software Engineer, Member of Technical Staff, VP Engineering, CTO Graduate research in: computer systems and architecture .