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Hyper Threading Concepts & Architecture

Hyperthreading – Concepts & Architecture

Agenda „

Technical Journey to Hyperthreading

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Hardware & Software Requirements

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Performance Issues

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Timeline Now, Parallel Computing is available on Single Processor

Cluster

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Symmetric Multi Processing (SMP)

Processor

Parallel Computing - Goals Parallel computing is when a program uses concurrency to either: „

decrease the runtime for the solution to a problem.

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Increase the size of the problem that can be solved.

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Single-threaded Processor Parts of Processor: „ Front-end: fetching/decoding/reordering „ Execution core: Concurrency actual execution Illusion „ „

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Multiple programs in memory Only one executes at a time „ 4-issue CPU with bubbles „ 7-unit CPU with pipeline bubbles Time-slicing via context switching

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Single-threaded SMP What is SMP? „ „

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Two threads execute at once, so threads spend less time waiting Twice as much speed and twice as much waste Hyperthreading

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“Symmetric MultiProcessors” Tolerably, mislabeled as “Shared-Memory Processors” Processors all connected to a (large) memory UMA: Uniform Memory Access, makes is easy to program Symmetric: all memory is equally close to all processors Cache Coherence via “snoopy caches”

Super-threading [Time-Slice Multithreading] „

Principle: the processor can execute more than one thread at a time

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Requires more hardware cleverness „ logic switches at each cycle

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Leads to less Waste „ Just a finer grain of interleaving

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BUT, each stage of the front end or the execution core only runs instructions from ONE thread!

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Does not help with poor instruction parallelism within one thread Hyperthreading

Simultaneous Multi Threading (SMT) „

Principle: the processor can execute more than one thread at a time, even within a single clock cycle!!

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Requires even more hardware cleverness „

logic switches within each cycle

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Finest level of interleaving

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From the OS perspective, there are two “logical” processors

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Evolution of Hyper-Threading „

Two ways of faster computing „ „

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Clock Speed cannot be increased beyond certain limit „

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Increase Clock Speed Better utilization of resources

Lot of heat generation

Better utilization of resources is now the choice „ „ „

Memory access takes relatively more time During this interval, CPU resources can be used by other threads This requires – Out-Of-Order Execution, Register Re-naming,...

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Hyper Threading With these points in mind, Intel came up with its version of Simultaneous Multi Threading (SMT) called Hyper Threading (HT)

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Hardware Requirements „

Because the additional threads all run on the same CPU elements (FPU, ALU) the only additions that are needed are the initial scheduling process.

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Although hyper-threading might seem like a pretty large departure from the kind of conventional, process-switching multithreading done on a single-threaded CPU, it actually doesn't add too much complexity to the hardware.

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Intel reports that adding hyper-threading to their Xeon processor added only 5% to its die area. Hyperthreading

Intel Xeon – Case Study „

Capable of executing at most two threads in parallel on two logical processors.

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Must be able to maintain information for two distinct and independent thread contexts.

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Done by dividing up the processor's micro-architectural resources into three types: „ „ „

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replicated partitioned shared

Intel Xeon – Resources Division •

Replicated

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Partitioned

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Shared

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Register renaming logic Instruction Pointer ITLB Return stack predictor Various other architectural registers

Re-order buffers (ROBs) Load/Store buffers Various queues, like the scheduling queues, uop queue, etc.

Caches: trace cache, L1, L2, L3 Micro-architectural registers Execution Units

Replicated Resources „

Some resources have to be replicated like „

Instruction Pointer „ „

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1 Instruction Pointer for each Logical Processor. Xeon: 2 Instruction Pointer

Register Allocation Table „

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For mapping architectural registers (8 integers and 8 floating-point) onto 128 General Purpose Registers and 128 Floating Point Registers Replicated Resource managing a Shared Resource

Partitioned Resources „

Queues are partitioned resources

Statically Partitioned Queue

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Dynamically Partitioned Queue

Shared Resources „

Heart of Hyperthreading: More Shared Resources => More Efficient Hyperthreading <= squeezing maximum amount of computing power out of the minimum amount of die space

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Such resources are: registers, load/store units

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SMT unaware

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Hyper-Threading Architecture Overview

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Confusing Notions Is Hyper-threaded Processor same as Dual Core? Answer: NO „ „

Hyper-Threaded = 2 Logical Processors Dual-Core = 2 Actual Processors on single chip

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HT – System Requirements „

HT enabled Processor „

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HT enabled Chipsets „

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Pentium 4 3.06 GHz, Xeon Intel 945G Express

HT enabled System BIOS HT enabled Operating System „

Windows 2000, XP, Linux 2.4.12

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HT – Requirements from User „ „

Enable HT in BIOS To utilize HT „

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Use multi-threaded applications OR Run multiple applications at same time

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Performance Issues - 1 „

2 Logical Processors != Double Power

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Lesser CPU intensive programs may not show much any gain

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Reported gains are 20-40%

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Performance Issues - 2 Death-Traps „ „ „

Main cause: Shared Resource Xeon Philosophy <->Cooperative Multitasking OS Cases: „

Floating Point Unit (FPU): „

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Cache „ „ „

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One floating-point intensive thread takes up the FPU; Another similar thread contending for same FPU gets stalled No cache-coherency problem as in SMP But, cache conflict between two logical processors Worst-Case: Two threads accessing different parts of memory and sharing no data => Lot of thrashing

Benchmarks Results: Non-SMT may perform better With the wrong mix of code, hyper-threading decreases performance

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HT Hardware Hands-On „

Need to Enable Hyperthreading through BIOS

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Simple Test: „ Do together with and without HT „ Compress 1GB File „ Play Windows Media Player with Visualization plug-in „ Analyze the time taken in 2 cases

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Good Benchmark: Embarrassing Parallel (EP) from NASA

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4 Processors View in Task Manager

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Key Point „

Hyper-Threading Technology gives better utilization of processor resources

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Hyper-Threading Technology gives more computing power for multithreaded applications Thread Level Parallelism on single processor

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References „ „

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"Hyper-Threading Technology." Intel. Deborah T. Marr, Frank Binns, David L. Hill, Glenn Hinton, David A. Koufaty, J. Alan Miller, Michael Upton. "Hyper-Threading Technology Architecture and Microarchitecture." Intel Susan Eggers, Hank Levy, Steve Gribble. Simultaneous Multithreading Project. University of Washington Susan Eggers, Joel Emer, Henry Levy, Jack Lo, Rebecca Stamm, and Dean Tullsen. "Simultaneous Multithreading: A Platform for Next-generation Processors." IEEE Micro, September/October 1997, pages 12-18. Jack Lo, Susan Eggers, Joel Emer, Henry Levy, Rebecca Stamm, and Dean Tullsen. "Converting Thread-Level Parallelism Into Instruction-Level Parallelism via Simultaneous Multithreading." ACM Transactions on Computer Systems, August 1997, pages 322-354.

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Hyperthreading