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Additive Synthesis on the T0 Vector Microprocessor


For my Master's project, I was working with the T0 / Torrent project, led by Prof. John Wawrzynek, writing an additive synthesis core for the T0 vector microprocessor. Co-contributers include Adrian Freed and David Wessel from the Center for New Music and Audio Technology (CNMAT), and John Hauser from CS.

The synthesizer is a software package that performs additive synthesis of music. It is written in a combination of C and assembly code to run on the SPERT boards installed in Sun workstations at ICSI (and elsewhere in the world). The additive technique produces sound by summing a group of sine waves (partials) at differing frequencies, amplitudes, and phases. This contrasts with techniques such as sampling, FM, physical modelling, or subtractive. The set of sine waves -- the sound -- is produced via this method because it is convieniently paired with a process called analysis/resynthesis,. During analysis, a set of sound sources are converted into a format --- called a spectral description -- that exposes the frequency content of the sounds and provides information about how they are spectrally related to one another. Then, during resysnthesis, these spectral descriptions are manipulated and combined in real-time by a performer to create fades, morphs, filtering, etc with very fine control over timbre.

We use various software at CNMAT to provide analysis and real-time manipulations (e.g., Adrian's "BYO"). The resulting input stream is sent to the synthesis software, and the sound from the synth sent to a D/A converter for output.

The key novel idea in our sythesizer was the recasting of the recursion equation for the sine computation, keeping error outside the bounds of auditory perception while minimizing the number of additional operations required to implement the modified equation on our hardware. Additionally, this technique is a good match to the vector-style architectures -- SIMD, VLIW, multimedia (small-data-type vector) ISA extensions like MMX -- that are becoming more common in advanced processors.

A nice short (4-page) version of the work is the ICASSP 1999 paper.


Sound Example

Here is a ten second tenor voice resynthesis with ten partials and 128 samples per frame. The first was generated using 32-bit IEEE floating-point for the filter, while the second uses the modified form for T0. Audibly the waveforms are indistinguishable, but physically they differ.

  • Floating-point tenor.aiff (900K)
  • Fixed-point tenor.aiff (900K)
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    Visual Example

    A square wave with 500 partials spanning from 20 to 19980Hz at 44.1KHz sampling rate. Square waves are nice visual examples because the error is easily estimated.


    Technical Abstract

    The most widely used digital sinusoidal oscillator structure employs a first order recursion to accumulate and wrap a phasor, followed by a sinusoidal functional evaluation - usually a table lookup. Second order recursions are an attractive alternative because the sinusoid is computed within the structure, avoiding the need for a large table or specialized hardware function evaluator. Unfortunately, numerous theoretical and practical challenges have to be overcome to use second order structures. We were motivated to overcome these because the next generation of microprocessors are hostile to efficient implementations of first order oscillators. Although primary cache memory may be large enough to hold a sine table, no locality of reference is observed for arbitrary frequencies. Good performance from vector microprocessors such as the "T0", "TigerSharc", "Altivec" and VLIW machines such as "Merced" requires exploitation of their strength - large multiply/add rate for on-chip data. The primary challenge with digital recursive structures is managing long-term stability, since rounding and truncation errors accumulate. In most applications frequency precision is the primary concern so the slow, long-term phase drift of first order oscillators can be ignored. Error accumulation is much more serious in second order structures and unfortunately the most efficient second order structure, the direct form I, is the most susceptible to debilitating instability at musically useful frequencies. This was particularly evident in our first implementations on T0, a microprocessor with a 16-bit fixed point vector arithmetic core. For this architecture we periodically recompute the state variables of the second order recursion at sufficient precision thereby eliminating error accumulation within the inner loop recursions. For these oscillators to be musically useful we also had to address the frequency precision problem, especially troublesome for low frequencies. A novel coefficient coding scheme and slightly more expensive filter structure solved this within perceptually significant bounds. An overlap/add strategy for the filter outputs addressed the final challenge - smoothly interpolated frequencies and amplitudes for banks of oscillators.

    Technical Abstract (another version)

    There are many benefits in the use of additive synthesis for sound production in computer music applications. The challenge of the technique is its voracious appetite for separately controllable sinusoidal partials. This paper summarizes our work developing a real-time additive synthesis engine supporting hundreds of simultaneous partials using the T0 vector microprocessor. The goal was to provide significantly more real-time partials than were available using conventional general-purpose hardware architectures. The major features of T0 that drive the design is the vector ISA and the use of fixed-point arithmetic. The explicit parallelism of the vector ISA led us to use parallel recursive oscillators. The 16b fixed-point arithmetic required adapting the recursive oscillators to provide additional accuracy. The modified oscillator is a two-pole filter that maintains frequency precision at a cost of one additional operation per filter sample. The new filter's error properties are expressly imperfect, explicitly matched to use in the context of digital audio (i.e., the human auditory system) rather than general-purpose applications. We briefly describe the controlling synthesizer software, the control structure for feeding the oscillators, fast initialization (needed for short additive synthesis windows), and applicability to related architectures. We present algorithm performance analysis and measurements of the implementation, focusing on how chip features affected algorithm design choices. The technique achieves 608 simultaneous real-time partials at 44.1KHz with the processor running at 40MHz and performing 8 operations per cycle (peak), or about 1.5 cycles per partial per sample.

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    Todd Hodes, <mylastname @ myfullname dot org>