Understanding the TigerSHARC ALU pipeline Determining the speed of one stage of IIR filter – Part 3 Understanding the memory pipeline issues

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 2 / 31 10/16/2015 Understanding the TigerSHARC ALU pipeline TigerSHARC has many pipelines Review of the COMPUTE pipeline works Interaction of memory (data) operations with COMPUTE operations  What we want to be able to do?  The problems we are expecting to have to solve  Using the pipeline viewer to see what really happens Changing code practices to get better performance  Specialized C++ compiler options and #pragmas (Will be covered by individual student presentation)  Optimized assembly code and optimized C++

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 3 / 31 10/16/2015 Processor Architecture bit data busses 2 Integer ALU 2 Computational Blocks  ALU (Float and integer)  SHIFTER  MULTIPLIER  COMMUNICATIONS CLU

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 4 / 31 10/16/2015 Simple Example IIR -- Biquad For (Stages = 0 to 3) Do  S0 = X in * H5 + S2 * H3 + S1 * H4  Y out = S0 * H0 + S1 * H1 + S2 * H2  S2 = S1  S1 = S0 S0 S1 S2 SO S1 S2

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 5 / 31 10/16/2015 PIPELINE STAGES See page 8-34 of Processor manual 10 pipeline stages, but may be completely desynchronized (happen semi- independently) Instruction fetch -- F1, F2, F3 and F4 Integer ALU – PreDecode, Decode, Integer, Access Compute Block – EX1 and EX2

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 6 / 31 10/16/2015 Instruction 0x17e XFR8 = R8 + R23 is STALLED (waiting) for 0x17d to complete XFR23 = R8 * R4 Bubble B means that the pipeline is doing “nothing” Meaning that the instruction shown is “place holder” (garbage)

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 7 / 31 10/16/2015 Code with stalls shown 8 code lines 5 expected stalls Expect 13 cycles to complete if theory is correct

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 8 / 31 10/16/2015 Analysis approach IS correct Code takes same time whether our “ SHOW-STALL instructions are there or not

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 9 / 31 10/16/2015 Process for coding for improved speed – code re-organization Make a copy of the code so can test iirASM( ) and iirASM_Optimized( ) to make sure get correct result Make a table of code showing ALU resource usage (paper, EXCEL, Project (Gantt chart) ) Identify data dependencies KEY – Make all “temp operations” use different register Move instructions “forward” to fill delay slots, BUT don’t break data dependencies

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 10 / 31 10/16/2015 Show resource usage and data dependencies

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 11 / 31 10/16/2015 Change all temporary registers to use different register names Then check code produces correct answer

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 12 / 31 10/16/2015 Move instructions forward, without breaking data dependencies What appears possible! DO one thing at a time and then check that code still works

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 13 / 31 10/16/2015 CHECK THE PIPELINE AFTER TESTING There are many more COMPUTE pipeline improvements possible. However, let’s not spend too much time here as we are only looking at half of the problem The coefficients are unlikely to be hard-coded, and the state variables can’t be if we are to call IIR( ) in a loop to be able to filter a series of values.

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 14 / 31 10/16/2015 Expect to take 8 cycles to execute This is not real life We must use IIR( ) in a loop in order to be able to filter a series of values. Also IIR( ) will involve multiple stages Means bring in (read) filter coefficients from memory. Means bring in (read) state values from memory and store (write) the changed state values at the end of the function.

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 15 / 31 10/16/2015 Rewrite Tests so that IIR( ) function can take parameters Lets make things real by passing in state variables through an “overloaded” C++ function

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 16 / 31 10/16/2015 Rewrite the “C++ code” I leave the old “fixed” values in until I can get the code to work. Proved useful this time as the code failed Why did it fail to return the correct value?

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 17 / 31 10/16/2015 Explore design issues – 1 What do we expect to have to worry about? XR0 = 0.0;// Set Fsum = 0; XR1 = [J1 += 1];// Fetch a coefficient from memory XFR2 = R1 * R4;// Multiply by Xinput (XR4) XFR0 = R0 + R2;// Add to sum XR3 = [J1 += 1];// Fetch a coefficient from memory XR5 = [J2 += 1];// Fetch a state value from memory XFR5 = R3 * R5;// Multiply coeff and state XFR0 = R0 + R5;// Perform a sum XR5 = XR12;// Update a state variable (dummy) XR12 = XR13 // Update a state variable (dummy) [J3 += 1] = XR12;// Store state variable to memory [J3 += 1] = XR5;// Store state variable to memory

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 18 / 31 10/16/2015 Explore design issues – 2 COMPUTE stalls expected (possible) XR0 = 0.0;// Set Fsum = 0; XR1 = [J1 += 1];// Fetch a coefficient from memory XFR2 = R1 * R4;// Multiply by Xinput (XR4) XFR0 = R0 + R2;// Add to sum XR3 = [J1 += 1];// Fetch a coefficient from memory XR5 = [J2 += 1];// Fetch a state value from memory XFR5 = R3 * R5;// Multiply coeff and state XFR0 = R0 + R5;// Perform a sum XR5 = XR12;// Update a state variable (dummy) XR12 = XR13 // Update a state variable (dummy) [J3 += 1] = XR12;// Store state variable to memory [J3 += 1] = XR5;// Store state variable to memory

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 19 / 31 10/16/2015 Explore design issues – 3 Probable memory stalls expected XR0 = 0.0;// Set Fsum = 0; XR1 = [J1 += 1];// Fetch a coefficient from memory XFR2 = R1 * R4;// Multiply by Xinput (XR4) XFR0 = R0 + R2;// Add to sum XR3 = [J1 += 1];// Fetch a coefficient from memory XR5 = [J2 += 1];// Fetch a state value from memory XFR5 = R3 * R5;// Multiply coeff and state XFR0 = R0 + R5;// Perform a sum XR5 = XR12;// Update a state variable (dummy) XR12 = XR13 // Update a state variable (dummy) [J3 += 1] = XR12;// Store state variable to memory [J3 += 1] = XR5;// Store state variable to memory

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 20 / 31 10/16/2015 Memory pipeline issues expected from COMPUTE pipeline issues seen When you start reading values from memory, how soon is the value fetched available for use within the COMPUTE? When you have adjacent memory accesses (read or write) does the pipeline work better (higher speed) with [J1 += 1];; or with [J1 += J4];; where J4 has been set to 1?

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 21 / 31 10/16/2015 Write a quick test to explore the code example

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 22 / 31 10/16/2015 Code stub – part copy from optimized IIR code

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 23 / 31 10/16/2015 What is the MINIMUM number of ;; that must be added so that the code is valid TigerSHARC (multi-instruction) code?

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 24 / 31 10/16/2015 Code assembles, put when it runs, it crashes the tests Neat mid-term question Explain why this code crashed the processor (corrupted the processor) so that the remaining tests never completed? What are the minimum numbers of lines that must be deleted or added to make the tests run (did not say work)

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 25 / 31 10/16/2015 Switched to simulator #if 0 / #endif around unnecessary tests Break point set at start of test code All ready seeing lots of pipeline issues Bigger picture on next slide

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 26 / 31 10/16/2015 Lots of instruction fetch issues PROBABLY from jumping into new routine and the instruction pipeline not filled by the start of this code Remove from this problem from the analysis by having 10 NOP;; at the beginning of this exploratory code WHY 10 NOPS and not 4?

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 27 / 31 10/16/2015 Looking much better.

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 28 / 31 10/16/2015 Pipeline issues – are they as we expected? COMPUTE operations – 1 cycle delay expected if next instruction needs the result of previous instruction When you start reading values from memory, how soon is the value fetched available for use within the COMPUTE? When you have adjacent memory accesses (read or write) does the pipeline work better with [J1 += 1];; or with [J1 += J4];; where J4 has been set to 1?

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 29 / 31 10/16/2015 Pipeline performance seen

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 30 / 31 10/16/2015 Pipeline performance predicted When you start reading values from memory, 1 cycle delay for value fetched available for use within the COMPUTE COMPUTE operations – 1 cycle delay expected if next instruction needs the result of previous instruction When you have adjacent memory accesses (read or write) does the pipeline work better with [J1 += 1];; or with [J1 += J4];; where J4 has been set to 1? [J1 += 1];; works just fine here (no delay). Worry about [J1 += J4];; another day

Speed IIR -- stage 3, M. Smith, ECE, University of Calgary, Canada 31 / 31 10/16/2015 Understanding the TigerSHARC ALU pipeline TigerSHARC has many pipelines Review of the COMPUTE pipeline works Interaction of memory (data) operations with COMPUTE operations  What we want to be able to do?  The problems we are expecting to have to solve  Using the pipeline viewer to see what really happens Changing code practices to get better performance  Can predict compute and memory stalls  Have enough information to be able to predict performance for real IIR code involving memory fetches and stores  Almost enough information to tackle Lab. 2 with IIR