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Intel’s MMX Dr. Richard Enbody CSE 820. Michigan State University Computer Science and Engineering Why MMX? Make the Common Case Fast Multimedia and Communication.

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Presentation on theme: "Intel’s MMX Dr. Richard Enbody CSE 820. Michigan State University Computer Science and Engineering Why MMX? Make the Common Case Fast Multimedia and Communication."— Presentation transcript:

1 Intel’s MMX Dr. Richard Enbody CSE 820

2 Michigan State University Computer Science and Engineering Why MMX? Make the Common Case Fast Multimedia and Communication consume significant computing resources. Providing specific hardware support makes sense.

3 Michigan State University Computer Science and Engineering Goals accelerate multimedia and communications applications. maintain full compatibility with existing operating systems and applications. exploit inherent parallelism in multimedia and communication algorithms includes new instructions and data types to improve performance.

4 Michigan State University Computer Science and Engineering First Step: examine code Examined a wide range of applications: graphics, MPEG video, music synthesis, speech compression, speech recognition, image processing, games, video conferencing. Identified and analyzed the most compute-intensive routines

5 Michigan State University Computer Science and Engineering Common Characteristics Small integer data types: e.g. 8-bit pixels, 16-bit audio samples Small, highly repetitive loops Frequent multiply-and-accumulate Compute-intensive algorithms Highly parallel operations

6 Michigan State University Computer Science and Engineering MMX Technology A set of basic, general purpose integer instructions: Single Instruction, Multiple Data (SIMD) 57 new instructions Eight 64-bit wide MMX registers Four new data types

7 Michigan State University Computer Science and Engineering Data Types

8 Michigan State University Computer Science and Engineering Data Types

9 Michigan State University Computer Science and Engineering Example Pixels are generally 8-bit integers. Pack eight pixels into a 64-bit MMX register. An MMX instruction takes all eight of the pixels at once from the MMX register, performs the arithmetic or logical operation on all eight elements in parallel, and writes the result into an MMX register.

10 Michigan State University Computer Science and Engineering Compatibility No new exceptions or states are added. Aliases to existing FP registers: The exponent field of the corresponding floating-point register (bits 64-78) and the sign bit (bit 79) are set to ones (1's), making the value in the register a NaN (Not a Number) or infinity when viewed as a floating-point value.

11 Michigan State University Computer Science and Engineering

12 Michigan State University Computer Science and Engineering 57 Instructions Basic arithmetic: add, subtract, multiply, arithmetic shift and multiply-add Comparison Conversion: pack & unpack Logical Shift Move: register-to-register Load/Store: 64-bit and 32-bit

13 Michigan State University Computer Science and Engineering Packed Add Word with wrap around Each Addition is independent Rightmost overflows and wraps around

14 Michigan State University Computer Science and Engineering Saturation Saturation: if addition results in overflow or underflow, the result is clamped to the largest or smallest value representable. This is important for pixel calculations where this would prevent a wrap-around add from causing a black pixel to suddenly turn white

15 Michigan State University Computer Science and Engineering No Mode There is no "saturation mode bit”: a new mode bit would require a change to the operating system. Separate instructions are used to generate wrap-around and saturating results.

16 Michigan State University Computer Science and Engineering Packed Add Word with unsigned saturation Each Addition is independent Rightmost saturates

17 Michigan State University Computer Science and Engineering Multiply-Accumulate multiply-accumulate operations are fundamental to many signal processing algorithms like vector-dot-products, matrix multiplies, FIR and IIR Filters, FFTs, DCTs etc

18 Michigan State University Computer Science and Engineering Packed Multiply-Add Multiply bytes generating four 32-bit results. Add the 2 products on the left for one result and the 2 products on the right for the other result.

19 Michigan State University Computer Science and Engineering Packed Parallel Compare No new condition code flags No existing IA condition code flags are affected by this instruction. Result can be used as a mask to select elements from different inputs using a logical operation, eliminating branchs.

20 Michigan State University Computer Science and Engineering Packed Parallel Compare

21 Michigan State University Computer Science and Engineering Pack/Unpack Important when an algorithm needs higher precision in its intermediate calculations, as in image filtering. For example, image filtering involves a set of intermediate multiply operations between filter coefficients and a set of adjacent image pixels, accumulating all the values together.

22 Michigan State University Computer Science and Engineering Pack

23 Michigan State University Computer Science and Engineering Conditional Select The Chroma Keying example demonstrates how conditional selection using the MMX instruction set removes branch mis-predictions, in addition to performing multiple selection operations in parallel. Text overlay on a pix/video background, and sprite overlays in games are some of the other operations that would benefit from this technique.

24 Michigan State University Computer Science and Engineering Chroma Keying

25 Michigan State University Computer Science and Engineering Chroma Keying (con’t) Take pixels from the picture with the woman on a green background. A compare instruction builds a mask for that data. That mask is a sequence of bytes that are all ones or all zeros. We now know what is the unwanted background and what we want to keep.

26 Michigan State University Computer Science and Engineering Create Mask Assume pixels alternate green/not_green

27 Michigan State University Computer Science and Engineering Combine: !AND, AND, OR

28 Michigan State University Computer Science and Engineering Branch Removal Without MMX technology, each pixel is processed separately and requires a conditional branch. Using MMX instructions, eight 8-bit pixels can be processed in parallel and no conditional branches are involved.

29 Michigan State University Computer Science and Engineering Vector Dot Product The vector dot product is one of the most basic algorithms used in signal- processing of natural data such as images, audio, video and sound. PMADD does 4 multiplies and 2 adds at a time. Coupled with PADD, eight multiply-accumulate operations can be performed: 2 PMADD and 2 PADD

30 Michigan State University Computer Science and Engineering Vector Dot Product

31 Michigan State University Computer Science and Engineering Vector Dot Product

32 Michigan State University Computer Science and Engineering Vector Dot Product Assuming precision is sufficient, a dot- product on an 8-element vector can be completed using 8 MMX instructions: 2 PMADDs, 2 PADDs, two shifts (if needed to fix the precision after the multiply), and 2 loads for one of the vectors (the other vector is loaded by the PMADD instruction which can have one of its operands come from memory).

33 Michigan State University Computer Science and Engineering Compare

34 Michigan State University Computer Science and Engineering Compare With MMX technology, one third of the number of instructions is needed. Most MMX instructions can be executed in one clock cycle, so the performance improvement will be more dramatic than the simple ratio of instruction counts.

35 Michigan State University Computer Science and Engineering Matrix Multiply 3D games: computations that manipulate 3D objects use 4-by-4 matrices that are multiplied with 4-element vectors many times. Each vector has the X,Y, Z and perspective corrective information for each pixel. The 4-by-4 matrix is used to rotate, scale, translate and update the perspective corrective information for each pixel.

36 Michigan State University Computer Science and Engineering

37 Michigan State University Computer Science and Engineering Compare

38 Michigan State University Computer Science and Engineering Matrix Multiply MMX required half the instructions.

39 Michigan State University Computer Science and Engineering Image Dissolve Using Alpha Blending Dissolve a Swan into a Flower Result_pixel = Flower_pixel * (alpha/255) + Swan_pixel * [1 - (alpha/255)] Assume 640x480 resolution

40 Michigan State University Computer Science and Engineering Dissolve: Millions of Inst.

41 Michigan State University Computer Science and Engineering Dissolve 1 billion fewer instructions for the 640x480 dissolve

42 Michigan State University Computer Science and Engineering

43 Michigan State University Computer Science and Engineering Conclusion MMX appeared in 1997 in Pentium processors (with bigger cache). According to Intel, an MMX microprocessor runs a multimedia application up to 60% faster. In addition, it runs other applications about 10% faster


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