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GPU-Accelerated Simulations


Uri Tal, CEO




               May 2, 2012
The User Challenge
Verification Bottleneck
Long verification process
  In 66% of designs, verification takes >50% of the design cycle
  In ~40% of projects, simulation regression runtime is longer than 1 day
Large design/SoC simulation challenge
  >40% of designs are larger than 10M gates
  Difficult to simulate the entire design/SoC
Excessive computing resources
  Required 10’s or 100’s GBytes of memory
  Needs most advanced CPUs                             Source: 2010 Wilson Research Group and
                                                     Mentor Graphics Functional Verification Study


 Effort spent on verification was increased by >58% in last 4 years

                                      May 2, 2012
Exploding Cost of Verification

$8.0B
$7.0B
$6.0B
$5.0B
$4.0B                                                            Engineering Cost
$3.0B                                                            Compute Farm
$2.0B
$1.0B
 $.0B
     2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
                                                              Source: Synopsys



                                      May 2, 2012
Functional Verification Solutions

   Simulation

   Emulation/Acceleration

   Formal Verification

   Others




                         May 2, 2012 4
                                   Slide:
Simulators using CPUs

  Event driven  single queue of events

  Memory access patterns  cache miss

  Multi-core CPUs:
   Only one order of magnitude
   Communication latency
   Limited bandwidth



                          May 2, 2012
HW Solutions
 Hardware accelerators and emulators
 are not simulators
     Suitable for system-level debug
     Are very expensive – HW cost, custom design
     Require significant effort for bring up
     Are limited in capacity (large designs require several boxes)


 They lack:
   Support for non-synthesizable code
   4-state-logic
   Full debug visibility


                                May 2, 2012
Simulations are Single-Threaded




                      May 2, 2012
The Cache becomes Useless




                   May 2, 2012
CPU Low Utilization

Thread #1   ALU        Memory Load          ALU        Memory Load




            Single thread + No “cache hit”  Low CPU Utilization




                                  May 2, 2012
A Brute-Force Approach




                 May 2, 2012
GPU Computing




                              Source: NVIDIA


                May 2, 2012
GPU Computing – cont’




 146X            36X          149X              50X             100X

Medical      Molecular        Financial   Matlab Computing   Astrophysics
Imaging      Dynamics        simulation     AccelerEyes         RIKEN
U of Utah   U of Illinois,     Oxford
              Urbana




                                                             Source: NVIDIA


                                May 2, 2012
The Power of GPU
     Peak Single Precision Performance
                 GFlops/sec
                  Tesla 20-series

      Tesla 10-series




      Tesla 8-
       series                 Nehalem
                               3 GHz




                                                       Source: NVIDIA

                                         May 2, 2012
GPU 100% Utilization


Thread #1     ALU          Memory Load          ALU          Memory Load

      Thread #2      ALU          Memory Load          ALU          Memory Load

            Thread #3       ALU          Memory Load          ALU          Memory Load

                    Thread #4      ALU          Memory Load          ALU          Memory Load

                           Thread #5      ALU         Memory Load           ALU        Memory Load




            Pipelining multiple threads can increase utilization to 100%


                                                   May 2, 2012
Logic Simulations - Challenge

– Billions of
  computing
  elements

– Short/simple
  calculations

– Many
  dependencies

– How to SIMD?

                      May 2, 2012
Breaking the Dependency
Barrier




                   May 2, 2012
Compilation Stages
           • Parse source files
           • RTL/Static Elaboration
Analyze



           • Create optimal dependency graphs
           • Calculate optimal GPU invocation schemes
Compile    • Generate skeleton (ske.v)




           • Calculate optimal memory allocation for variables
           • Generate final recipes for the GPU virtual machine
Assembly




                                                May 2, 2012
Distributed Compilation




                  May 2, 2012
Co-Simulation Approach




                   May 2, 2012
RocketSim™ Overview
Summary
Highly-cost-effective simulation offload-engine, based on GPUs

10x acceleration factor compared to Cadence ncsim & Synopsys vcs

Acceleration increases with every new GPU generation

Works seamlessly with every existing simulator (Cadence, Synopsys, …)

Zero ramp-up time

Supports extremely huge designs (Giga-gates)

Short compilation time (minutes)

Full visibility


                                        May 2, 2012
Customers testimonials
“With RocketSim, simulation time was reduced dramatically from
weeks to days, with a tenfold increase in speed and five-fold
decrease in server RAM requirements. This, together with support
of 4-state and capacity of more than 1G gates, give us a superb
tool to simulate our next generation GPU designs.”
                             - Dan Smith, Director of Engineering, NVIDIA


"Rocketick's RocketSim™ simulation accelerator solved verification
bottleneck of our SwitchX® switch silicon IC project by running
37 days’ worth of simulation over a single weekend without
changes in our standard verification environment and scripts. In
addition, reducing memory consumption from 192GB to less than
8GB allowed full chip simulation of SwitchX®, which was
previously impossible using standard simulators."
                             - Eitan Zahavi, Senior Director of
Engineering, Mellanox



                               May 2, 2012
Thank you for your time
     For more information:
      www.rocketick.com




              May 2, 2012

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Rocketick accelerated verilog simulations

  • 2. The User Challenge Verification Bottleneck Long verification process  In 66% of designs, verification takes >50% of the design cycle  In ~40% of projects, simulation regression runtime is longer than 1 day Large design/SoC simulation challenge  >40% of designs are larger than 10M gates  Difficult to simulate the entire design/SoC Excessive computing resources  Required 10’s or 100’s GBytes of memory  Needs most advanced CPUs Source: 2010 Wilson Research Group and Mentor Graphics Functional Verification Study Effort spent on verification was increased by >58% in last 4 years May 2, 2012
  • 3. Exploding Cost of Verification $8.0B $7.0B $6.0B $5.0B $4.0B Engineering Cost $3.0B Compute Farm $2.0B $1.0B $.0B 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Source: Synopsys May 2, 2012
  • 4. Functional Verification Solutions Simulation Emulation/Acceleration Formal Verification Others May 2, 2012 4 Slide:
  • 5. Simulators using CPUs Event driven  single queue of events Memory access patterns  cache miss Multi-core CPUs:  Only one order of magnitude  Communication latency  Limited bandwidth May 2, 2012
  • 6. HW Solutions Hardware accelerators and emulators are not simulators  Suitable for system-level debug  Are very expensive – HW cost, custom design  Require significant effort for bring up  Are limited in capacity (large designs require several boxes) They lack:  Support for non-synthesizable code  4-state-logic  Full debug visibility May 2, 2012
  • 8. The Cache becomes Useless May 2, 2012
  • 9. CPU Low Utilization Thread #1 ALU Memory Load ALU Memory Load Single thread + No “cache hit”  Low CPU Utilization May 2, 2012
  • 10. A Brute-Force Approach May 2, 2012
  • 11. GPU Computing Source: NVIDIA May 2, 2012
  • 12. GPU Computing – cont’ 146X 36X 149X 50X 100X Medical Molecular Financial Matlab Computing Astrophysics Imaging Dynamics simulation AccelerEyes RIKEN U of Utah U of Illinois, Oxford Urbana Source: NVIDIA May 2, 2012
  • 13. The Power of GPU Peak Single Precision Performance GFlops/sec Tesla 20-series Tesla 10-series Tesla 8- series Nehalem 3 GHz Source: NVIDIA May 2, 2012
  • 14. GPU 100% Utilization Thread #1 ALU Memory Load ALU Memory Load Thread #2 ALU Memory Load ALU Memory Load Thread #3 ALU Memory Load ALU Memory Load Thread #4 ALU Memory Load ALU Memory Load Thread #5 ALU Memory Load ALU Memory Load Pipelining multiple threads can increase utilization to 100% May 2, 2012
  • 15. Logic Simulations - Challenge – Billions of computing elements – Short/simple calculations – Many dependencies – How to SIMD? May 2, 2012
  • 17. Compilation Stages • Parse source files • RTL/Static Elaboration Analyze • Create optimal dependency graphs • Calculate optimal GPU invocation schemes Compile • Generate skeleton (ske.v) • Calculate optimal memory allocation for variables • Generate final recipes for the GPU virtual machine Assembly May 2, 2012
  • 18. Distributed Compilation May 2, 2012
  • 19. Co-Simulation Approach May 2, 2012
  • 20. RocketSim™ Overview Summary Highly-cost-effective simulation offload-engine, based on GPUs 10x acceleration factor compared to Cadence ncsim & Synopsys vcs Acceleration increases with every new GPU generation Works seamlessly with every existing simulator (Cadence, Synopsys, …) Zero ramp-up time Supports extremely huge designs (Giga-gates) Short compilation time (minutes) Full visibility May 2, 2012
  • 21. Customers testimonials “With RocketSim, simulation time was reduced dramatically from weeks to days, with a tenfold increase in speed and five-fold decrease in server RAM requirements. This, together with support of 4-state and capacity of more than 1G gates, give us a superb tool to simulate our next generation GPU designs.” - Dan Smith, Director of Engineering, NVIDIA "Rocketick's RocketSim™ simulation accelerator solved verification bottleneck of our SwitchX® switch silicon IC project by running 37 days’ worth of simulation over a single weekend without changes in our standard verification environment and scripts. In addition, reducing memory consumption from 192GB to less than 8GB allowed full chip simulation of SwitchX®, which was previously impossible using standard simulators." - Eitan Zahavi, Senior Director of Engineering, Mellanox May 2, 2012
  • 22. Thank you for your time For more information: www.rocketick.com May 2, 2012