Hazardless Processor Architecture Without Register Renaming
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Review Memory Disambiguation Review Explicit Register Renaming
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Data-Flow Prescheduling for Large Instruction Windows in Out-Of-Order Processors
Data-Flow Prescheduling for Large Instruction Windows in Out-of-Order Processors Pierre Michaud, Andr´e Seznec IRISA/INRIA Campus de Beaulieu, 35042 Rennes Cedex, France {pmichaud, seznec}@irisa.fr Abstract We introduce data-flow prescheduling. Instructions are sent to the issue buffer in a predicted data-flow order instead The performance of out-of-order processors increases of the sequential order, allowing a smaller issue buffer. The with the instruction window size. In conventional proces- rationale of this proposal is to avoid using entries in the is- sors, the effective instruction window cannot be larger than sue buffer for instructions which operands are known to be the issue buffer. Determining which instructions from the yet unavailable. issue buffer can be launched to the execution units is a time- In our proposal, this reordering of instructions is accom- critical operation which complexity increases with the issue plished through an array of schedule lines. Each schedule buffer size. We propose to relieve the issue stage by reorder- line corresponds to a different depth in the data-flow graph. ing instructions before they enter the issue buffer. This study The depth of each instruction in the data-flow graph is de- introduces the general principle of data-flow prescheduling. termined, and the instruction is inserted in the correspond- Then we describe a possible implementation. Our prelim- ing schedule line. Lines are consumed by the issue buffer inary results show that data-flow prescheduling makes it sequentially. possible to enlarge the effective instruction window while Section 2 briefly describes issue buffers and discusses re- keeping the issue buffer small. -
Jetson TX2 • NVIDIA Jetson Xavier • GPU Programming • Algorithm Mapping: • Convolutions Parallel Algorithm Execution
GPU and multicore CPU architectures. Algorithm mapping Contributors: N. Tsapanos, I. Karakostas, I. Pitas Aristotle University of Thessaloniki, Greece Presenter: Prof. Ioannis Pitas Aristotle University of Thessaloniki [email protected] www.multidrone.eu Presentation version 1.3 GPU and multicore CPU architectures. Algorithm mapping • GPU and multicore CPU processing boards • Graphics cards • NVIDIA Jetson TX2 • NVIDIA Jetson Xavier • GPU programming • Algorithm mapping: • Convolutions Parallel algorithm execution • Graphics computing: • Highly parallelizable • Linear algebra parallelization: • Vector inner products: 푐 = 풙푇풚. • Matrix-vector multiplications 풚 = 푨풙. • Matrix multiplications: 푪 = 푨푩. Parallel algorithm execution • Convolution: 풚 = 푨풙 • CNN architectures, linear systems, signal filtering. • Correlation: 풚 = 푨풙 • template matching, tracking. • Signal transforms (DFT, DCT, Haar, etc): • Matrix vector product form: 푿 = 푾풙 • 2D transforms (matrix product form): 푿’ = 푾푿. Processing Units • Multicore (CPU): • MIMD. • Focused on latency. • Best single thread performance. • Manycore (GPU): • SIMD. • Focused on throughput. • Best for embarrassingly parallel tasks. Pascal microarchitecture https://devblogs.nvidia.com/inside-pascal/gp100_block_diagram-2/ Pascal microarchitecture https://devblogs.nvidia.com/inside-pascal/gp100_sm_diagram/ GeForce GTX 1080 • Microarchitecture: Pascal. • DRAM: 8 GB GDDR5X at 10000 MHz. • SMs: 20. • Memory bandwidth: 320 GB/s. • CUDA cores: 2560. • L2 Cache: 2048 KB. • Clock (base/boost): 1607/1733 MHz. • L1 Cache: 48 KB per SM. • GFLOPs: 8873. • Shared memory: 96 KB per SM. GPU and multicore CPU architectures. Algorithm mapping • GPU and multicore CPU processing boards • Graphics cards • NVIDIA Jetson TX2 • NVIDIA Jetson Xavier • GPU programming • Algorithm mapping: • Convolutions ARM Cortex-A57: High-End ARMv8 CPU • ARMv8 architecture • Architecture evolution that extends ARM’s applicability to all markets. • Full ARM 32-bit compatibility, streamlined 64-bit capability. -
ARM Cortex-A* Brian Eccles, Riley Larkins, Kevin Mee, Fred Silberberg, Alex Solomon, Mitchell Wills
ARM Cortex-A* Brian Eccles, Riley Larkins, Kevin Mee, Fred Silberberg, Alex Solomon, Mitchell Wills The ARM CortexA product line has changed significantly since the introduction of the CortexA8 in 2005. ARM’s next major leap came with the CortexA9 which was the first design to incorporate multiple cores. The next advance was the development of the big.LITTLE architecture, which incorporates both high performance (A15) and high efficiency(A7) cores. Most recently the A57 and A53 have added 64bit support to the product line. The ARM Cortex series cores are all made up of the main processing unit, a L1 instruction cache, a L1 data cache, an advanced SIMD core and a floating point core. Each processor then has an additional L2 cache shared between all cores (if there are multiple), debug support and an interface bus for communicating with the rest of the system. Multicore processors (such as the A53 and A57) also include additional hardware to facilitate coherency between cores. The ARM CortexA57 is a 64bit processor that supports 1 to 4 cores. The instruction pipeline in each core supports fetching up to three instructions per cycle to send down the pipeline. The instruction pipeline is made up of a 12 stage in order pipeline and a collection of parallel pipelines that range in size from 3 to 15 stages as seen below. The ARM CortexA53 is similar to the A57, but is designed to be more power efficient at the cost of processing power. The A57 in order pipeline is made up of 5 stages of instruction fetch and 7 stages of instruction decode and register renaming. -
Out-Of-Order Execution & Register Renaming
Asanovic/Devadas Spring 2002 6.823 Out-of-Order Execution & Register Renaming Krste Asanovic Laboratory for Computer Science Massachusetts Institute of Technology Asanovic/Devadas Spring 2002 6.823 Scoreboard for In-order Issue Busy[unit#] : a bit-vector to indicate unit’s availability. (unit = Int, Add, Mult, Div) These bits are hardwired to FU's. WP[reg#] : a bit-vector to record the registers for which writes are pending Issue checks the instruction (opcode dest src1 src2) against the scoreboard (Busy & WP) to dispatch FU available? not Busy[FU#] RAW? WP[src1] or WP[src2] WAR? cannot arise WAW? WP[dest] Asanovic/Devadas Spring 2002 Out-of-Order Dispatch 6.823 ALU Mem IF ID Issue WB Fadd Fmul • Issue stage buffer holds multiple instructions waiting to issue. • Decode adds next instruction to buffer if there is space and the instruction does not cause a WAR or WAW hazard. • Any instruction in buffer whose RAW hazards are satisfied can be dispatched (for now, at most one dispatch per cycle). On a write back (WB), new instructions may get enabled. Asanovic/Devadas Spring 2002 6.823 Out-of-Order Issue: an example latency 1 LD F2, 34(R2) 1 1 2 2 LD F4, 45(R3) long 3 MULTD F6, F4, F2 3 4 3 4 SUBD F8, F2, F2 1 5 5 DIVD F4, F2, F8 4 6 ADDD F10, F6, F4 1 6 In-order: 1 (2,1) . 2 3 4 4 3 5 . 5 6 6 Out-of-order: 1 (2,1) 4 4 . 2 3 . 3 5 . -
Dynamic Register Renaming Through Virtual-Physical Registers
Dynamic Register Renaming Through Virtual-Physical Registers † Teresa Monreal [email protected] Antonio González* [email protected] Mateo Valero* [email protected] †† José González [email protected] † Víctor Viñals [email protected] †Departamento de Informática e Ing. de Sistemas. Centro Politécnico Superior - Univ. de Zaragoza, Zaragoza, Spain. *Departament d’ Arquitectura de Computadors. Universitat Politècnica de Catalunya, Barcelona, Spain. ††Departamento de Ingeniería y Tecnología de Computadores. Universidad de Murcia, Murcia, Spain. Abstract Register file access time represents one of the critical delays of current microprocessors, and it is expected to become more critical as future processors increase the instruction window size and the issue width. This paper present a novel dynamic register renaming scheme that delays the allocation of physical registers until a late stage in the pipeline. We show that it can provide important savings in number of physical registers so it can significantly shorter the register file access time. Delaying the allocation of physical registers requires some artifact to keep track of dependences. This is achieved by introducing the concept of virtual-physical registers, which are tags that do not require any storage location. The proposed renaming scheme shortens the average number of cycles that each physical register is allocated, and allows for an early execution of instructions since they can obtain a physical register for its destination earlier than with the conventional scheme. Early execution is especially beneficial for branches and memory operations, since the former can be resolved earlier and the latter can prefetch their data in advance. 1. Introduction Dynamically-scheduled superscalar processors exploit instruction-level parallelism (ILP) by overlapping the execution of instructions in an instruction window. -
Computer Architecture Out-Of-Order Execution
Computer Architecture Out-of-order Execution By Yoav Etsion With acknowledgement to Dan Tsafrir, Avi Mendelson, Lihu Rappoport, and Adi Yoaz 1 Computer Architecture 2013– Out-of-Order Execution The need for speed: Superscalar • Remember our goal: minimize CPU Time CPU Time = duration of clock cycle × CPI × IC • So far we have learned that in order to Minimize clock cycle ⇒ add more pipe stages Minimize CPI ⇒ utilize pipeline Minimize IC ⇒ change/improve the architecture • Why not make the pipeline deeper and deeper? Beyond some point, adding more pipe stages doesn’t help, because Control/data hazards increase, and become costlier • (Recall that in a pipelined CPU, CPI=1 only w/o hazards) • So what can we do next? Reduce the CPI by utilizing ILP (instruction level parallelism) We will need to duplicate HW for this purpose… 2 Computer Architecture 2013– Out-of-Order Execution A simple superscalar CPU • Duplicates the pipeline to accommodate ILP (IPC > 1) ILP=instruction-level parallelism • Note that duplicating HW in just one pipe stage doesn’t help e.g., when having 2 ALUs, the bottleneck moves to other stages IF ID EXE MEM WB • Conclusion: Getting IPC > 1 requires to fetch/decode/exe/retire >1 instruction per clock: IF ID EXE MEM WB 3 Computer Architecture 2013– Out-of-Order Execution Example: Pentium Processor • Pentium fetches & decodes 2 instructions per cycle • Before register file read, decide on pairing Can the two instructions be executed in parallel? (yes/no) u-pipe IF ID v-pipe • Pairing decision is based… On data -
CSC.T433 Advanced Computer Architecture, Department of Computer Science, TOKYO TECH 1 Datapath of Ooo Execution Processor
Fiscal Year 2020 Ver. 2021-01-25a Course number: CSC.T433 School of Computing, Graduate major in Computer Science Advanced Computer Architecture 10. Multi-Processor: Distributed Memory and Shared Memory Architecture www.arch.cs.titech.ac.jp/lecture/ACA/ Room No.W936 Kenji Kise, Department of Computer Science Mon 14:20-16:00, Thr 14:20-16:00 kise _at_ c.titech.ac.jp CSC.T433 Advanced Computer Architecture, Department of Computer Science, TOKYO TECH 1 Datapath of OoO execution processor Instruction flow Instruction cache Branch handler Instruction fetch Instruction decode Renaming Register file Dispatch Integer Floating-point Memory Memory dataflow RS Instruction window ALU ALU Branch FP ALU Adr gen. Adr gen. Store Reorder buffer (ROB) queue Data cache Register dataflow CSC.T433 Advanced Computer Architecture, Department of Computer Science, TOKYO TECH Reservation station (RS) 2 Growth in clock rate of microprocessors From CAQA 5th edition CSC.T433 Advanced Computer Architecture, Department of Computer Science, TOKYO TECH 3 From multi-core era to many-core era Single-ISA Heterogeneous Multi-Core Architectures: The Potential for Processor Power Reduction, MICRO-36 CSC.T433 Advanced Computer Architecture, Department of Computer Science, TOKYO TECH 4 Aside: What is a window? • A window is a space in the wall of a building or in the side of a vehicle, which has glass in it so that light can come in and you can see out. (Collins) Instruction window 8 6 5 4 7 (a) Instruction window Instructions to be executed for an application Large instruction -
Hardware-Sensitive Database Operations - II
Faculty of Computer Science Database and Software Engineering Group Hardware-Sensitive Database Operations - II Balasubramanian (Bala) Gurumurthy Advanced Topics in Databases, 2019/May/17 Otto-von-Guericke University of Magdeburg So Far... ● Hardware evolution and current challenges ● Hardware-oblivious vs. hardware-sensitive programming ● Pipelining in RISC computing ● Pipeline Hazards ○ Structural hazard ○ Data hazard ○ Control hazard ● Resolving hazards ○ Loop-Unrolling ○ Predication Bala Gurumurthy | Hardware-Sensitive Database Operations Part II We will see ● Vectorization ○ SIMD Execution ○ SIMD in DBMS Operation ● GPUs in DBMSs ○ Processing Model ○ Handling Synchronization Bala Gurumurthy | Hardware-Sensitive Database Operations Vectorization Leveraging Modern Processing Capabilities Hardware Parallelism One we know already: Pipelining ● Separate chip regions for individual tasks to execute independently ● Advantage: parallelism + sequential execution semantics ● We discussed problems of hazards ● VLSI tech. limits degree up to which pipelining is feasible [Kaeslin, 2008] Bala Gurumurthy | Hardware-Sensitive Database Operations Hardware Parallelism Chip area can be used for other types of parallelism: Computer systems typically use identical hardware circuits, but their function may be controlled by different instruction stream Si: Bala Gurumurthy | Hardware-Sensitive Database Operations Special instances Example of this architecture? Bala Gurumurthy | Hardware-Sensitive Database Operations Special instances Example of this architecture? -
Trends in Processor Architecture
A. González Trends in Processor Architecture Trends in Processor Architecture Antonio González Universitat Politècnica de Catalunya, Barcelona, Spain 1. Past Trends Processors have undergone a tremendous evolution throughout their history. A key milestone in this evolution was the introduction of the microprocessor, term that refers to a processor that is implemented in a single chip. The first microprocessor was introduced by Intel under the name of Intel 4004 in 1971. It contained about 2,300 transistors, was clocked at 740 KHz and delivered 92,000 instructions per second while dissipating around 0.5 watts. Since then, practically every year we have witnessed the launch of a new microprocessor, delivering significant performance improvements over previous ones. Some studies have estimated this growth to be exponential, in the order of about 50% per year, which results in a cumulative growth of over three orders of magnitude in a time span of two decades [12]. These improvements have been fueled by advances in the manufacturing process and innovations in processor architecture. According to several studies [4][6], both aspects contributed in a similar amount to the global gains. The manufacturing process technology has tried to follow the scaling recipe laid down by Robert N. Dennard in the early 1970s [7]. The basics of this technology scaling consists of reducing transistor dimensions by a factor of 30% every generation (typically 2 years) while keeping electric fields constant. The 30% scaling in the dimensions results in doubling the transistor density (doubling transistor density every two years was predicted in 1975 by Gordon Moore and is normally referred to as Moore’s Law [21][22]). -
STRAIGHT: Realizing a Lightweight Large Instruction Window by Using Eventually Consistent Distributed Registers
2012 Third International Conference on Networking and Computing STRAIGHT: Realizing a Lightweight Large Instruction Window by using Eventually Consistent Distributed Registers Hidetsugu IRIE∗, Daisuke FUJIWARA∗, Kazuki MAJIMA∗, Tsutomu YOSHINAGA∗ ∗The University of Electro-Communications 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan E-mail: [email protected], [email protected], [email protected], [email protected] Abstract—As the number of cores as well as the network size programs. For scale-out applications, we assume the manycore in a processor chip increases, the performance of each core is processor structure, which consists of a number of STRAIGHT more critical for the improvement of the total chip performance. architecture cores (SAC) that are loosely connected each other. However, to improve the total chip performance, the performance per power or per unit area must be improved, making it difficult Being the first report on this novel processor architecture, in to adopt a conventional approach of superscalar extension. In this paper, we discuss the concept behind STRAIGHT, propose this paper, we explore a new core structure that is suitable for basic principles, and estimate the performance and budget manycore processors. We revisit prior studies of new instruction- expectation. The rest of the paper consists of following sec- level (ILP) and thread-level parallelism (TLP) architectures tions. Section II revisits studies of new architectures that were and propose our novel STRAIGHT processor architecture. By introducing the scheme of distributed key-value-store to the designed to improve the ILP/TLP performance of superscalar register file of clustered microarchitectures, STRAIGHT directly processors, and discusses the dilemma of both scalability executes the operation with large logical registers, which are approach and quick worker approach. -
WCAE 2003 Workshop on Computer Architecture Education
WCAE 2003 Proceedings of the Workshop on Computer Architecture Education in conjunction with The 30th International Symposium on Computer Architecture DQG 2003 Federated Computing Research Conference Town and Country Resort and Convention Center b San Diego, California June 8, 2003 Workshop on Computer Architecture Education Sunday, June 8, 2003 Session 1. Welcome and Keynote 8:45–10:00 8:45 Welcome Edward F. Gehringer, workshop organizer 8:50 Keynote address, “Teaching and teaching computer Architecture: Two very different topics (Some opinions about each),” Yale Patt, teacher, University of Texas at Austin 1 Break 10:00–10:30 Session 2. Teaching with New Architectures 10:30–11:20 10:30 “Intel Itanium floating-point architecture,” Marius Cornea, John Harrison, and Ping Tak Peter Tang, Intel Corp. ................................................................................................................................. 5 10:50 “DOP — A CPU core for teaching basics of computer architecture,” Miloš BeþváĜ, Alois Pluháþek and JiĜí DanƟþek, Czech Technical University in Prague ................................................................. 14 11:05 Discussion Break 11:20–11:30 Session 3. Class Projects 11:30–12:30 11:30 “Superscalar out-of-order demystified in four instructions,” James C. Hoe, Carnegie Mellon University ......................................................................................................................................... 22 11:50 “Bridging the gap between undergraduate and graduate experience in