1. Design of A Custom Vector Operation API Exploiting SIMD Intrinsics within Java Presented by John-Marc Desmarais Authors: Jonathan Parri, John-Marc Desmarais, Daniel Shapiro, Miodrag Bolic and Voicu Groza

2. Overview  Introduction  What is SIMD?  jSIMD Userflow  Issues and Considerations  Java Native Interface  Current Implementation  Results  Future Work  Conclusion carg.site.uottawa.ca CARG 2010

3. Introduction carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Many embedded systems have begun to take advantage of the Java framework. JVMs can be embedded or rest on top of the OS. SIMD is an often under utilized option available on many processors. (O3 compilation) In Java it is up to the JVM to best decide how to use SIMD if available at runtime. CARG 2010

4. SIMD carg.site.uottawa.ca CARG 2010 Functional Unit … Data Multiple processing elements that performs the same operation on data simultaneously. Single Instruction Multiple Data Instruction

5. Common SIMD Implementations AMD 3DNow! Intel MMX SSE (Streaming SIMD Extensions) AltiVec from Apple, IBM and Freescale VIS from Sun Microsystems x86/x64 PowerPC SPARC xmm1 xmm0 xmm3 xmm2 128 bits

6. jSIMD: User Flow carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Current SIMD Optimization Java Flow CARG 2010 jSIMD SIMD Optimization Approach Standard Java Profile at Runtime Change Java Code Runtime JVM to SIMD MappingMay take very long or may not even achieve best SIMD usage Standard Java with jSIMD

7. Issues & Considerations carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Packing Packaging and aligning data into SIMD registers is very time consuming. Transactional Intermediate values should not leave SIMD memory and register space. Target Specifics Various targets have different SIMD implementations. (May not even exist, fallback) CARG 2010

8. jSIMD: SIMD for Java carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Java and the JNI Java allows programs to use native libraries. SIMD instructions can be called manually from native code. Solution! Map all SIMD intrinsic into JNI making them invisible to the Java programmer. No system specific code/headers are permitted in the library so compilation can be performed automatically on any platform. CARG 2010

9. jSIMD: SIMD for Java carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Current Implementation Running Targets: Intel x86/x64 AMD x86/x64 SPARC PowerPC Future Targets: NIOS II with custom SIMD Unit CARG 2010

10. jSIMD: User Perspective carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Extended Java ISA with parallel SIMD operations. Native operations hidden as Java methods. User is not concerned with native interface. Transparency CARG 2010 Java Base Java ISA jSIMD API Native SIMD Mappings in C

11. Results carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) JVM versus Programmer Know-How CARG 2010 JVM does an impressive job at SIMD mapping but is not as effective as a determined programmer with an understanding of the underlying target architecture.

12. Results CARG 2010

13. Design Space Exploration carg.site.uottawa.ca Multiprocessors (Add more processors) Memory Hierarchy Coprocessors & Hardware Accelerators Multi-Core Interconnect Topology SIMD (Single Instruction Multiple Data) ISE (Instruction Set Extensions) CARG 2010 GPU (Graphical Processing Units)

14. Future Work carg.site.uottawa.ca SIMD (Single Instruction Multiple Data) Future as DSE Avenue Manual Specification and Automatic Detection for Native SIMD Rewrite Java for jSIMD VectorizeAnalysisProfile PARRI:CARG 2010

15. Conclusion PARRI:CARG 2010 carg.site.uottawa.ca VMs should integrate this approach into their languages. Until such time as VM support is made available, programmers can use our API to accelerate their applications. We have shown that jSIMD can be used to accelerate VM-based applications more effectively than contemporary automated solutions.