Hugh C. Lauer

The VolumePro real-time ray-casting system

This paper describes VolumePro, the world’s first single-chip realtime volume rendering system for consumer PCs. VolumePro implements ray-casting with parallel slice-by-slice processing. Our discussion of the architecture focuses mainly on the rendering pipeline and the memory organization. VolumePro has hardware for gradient estimation, classification, and per-sample Phong illumination. The system does not perform any pre-processing and makes parameter adjustments and changes to the volume data immediately visible. We describe several advanced features of VolumePro, such as gradient magnitude modulation of opacity and illumination, supersampling, cropping and cut planes. The system renders 500 million interpolated, Phong illuminated, composited samples per second. This is sufficient to render volumes with up to 16 million voxels (e.g., 256) at 30 frames per second. CR Categories: B.4.2 [Hardware]: Input/Output and Data Communications—Input/Output DevicesImage display; C.3 [Computer Systems Organization]: Special-Purpose and ApplicationBased Systems—Real-time and embedded systems; I.3.1 [Computer Graphics]: Hardware Architecture—Graphics processor;

A program structure for error detection and recovery

The paper describes a method of structuring programs which aids the design and validation of facilities for the detection of and recovery from software errors. Associated with the method is a mechanism for the automatic preservation of restart information at a level of overhead which is believed to be tolerable.

Simulating arthroscopic knee surgery using volumetric object representations, real-time volume rendering and haptic feedback

A system for simulating arthroscopic knee surgery that is based on volumetric object models derived from 3D Magnetic Resonance Imaging is presented. Feedback is provided to the user via real-time volume rendering and force feedback for haptic exploration. The system is the result of a unique collaboration between an industrial research laboratory, two major universities, and a leading research hospital. In this paper, components of the system are detailed and the current state of the integrated system is presented. Issues related to future research and plans for expanding the current system are discussed.

Volumetric Object Modeling for Surgical Simulation

Surgical simulation has many applications in medical education, surgical training, surgical planning and intra-operative assistance. However, extending current surface-based computer graphics methods to model phenomena such as the deformation, cutting, tearing or repairing of soft tissues poses significant challenges for real-time interactions. This paper discusses the use of volumetric methods for modeling complex anatomy and tissue interactions. New techniques are introduced that use volumetric methods for modeling soft-tissue deformation and tissue cutting at interactive rates. An initial prototype for simulating arthroscopic knee surgery is described which uses volumetric models of the knee derived from 3-D magnetic resonance imaging, visual feedback via real-time volume and polygon rendering, and haptic feedback provided by a force-feedback device.

EM-Cube: an architecture for low-cost real-time volume rendering

EM-Cube is a VLSI architecture for low-cost, high quality volume rendering at full video frame rates. Derived from the Cube4 architecture developed at SUNY at Stony Brook, EM-Cube computes sample points and gradients on-the-fly to project 3-dimensional volume dnta onto 2-dimensional images with realistic lighting and shading. A modest rendering system based on EM-Cube consists of a PC1 card with four rendering chips (ASICs), four 64Mbit SDRAMs to hold the volume data, and four SRAMs to capture the rendered image. The performance target for this configuration is to render images from a 25G3 x 16 bit data set at 30 fmmes/sec. The EM-Cube architecture can be scaled to larger volume data-sets and/or higher frame rates by adding additional ASKS, SDRAMs, and SRAMs. This paper addresses three major challenges encountered developing EM-Cube into a pm&al product: exploiting the bandwidth inherent in the SDRAMs containing the volume data, keeping the pin-count between adjacent ASICs at a tractable level, and reducing the on-chip stomge required to hold the intermediate results of rendering.

A recursive virtual machine architecture

This paper summarizes the preliminary design of a computer system with a recursive, virtual machine architecture and gives a brief account of the considerations leading to that design . In this system, each process operates in its own address space, called its virtual memory, and can create other processes within its space and pass control to them. The newly create d processes can, recursively, create their own descendants without the knowledge or assistance of a supervisor. There is no “privileged” or “supervisor” state; protection is provided entirely by the virtual memory mechanism, and each interrupt is directed by hardware to the process designated to handle it. Virtual memories are segmented; moreover, paging is treated as a recursive application of segmentation and can occur at any level. The machine architecture encourages modular and hierarchical approaches to program design because of the high degree of protection afforded by the creation of new virtual memories at low cost.

Shear-image order ray casting volume rendering

This paper describes shear-image order ray casting, a new method for volume rendering. This method renders sampled data in three dimensions with image quality equivalent to the best of ray-per-pixel volume rendering algorithms (full image order), while at the same time retaining computational complexity and spatial coherence near to that of the fastest known algorithm (shear-warp). In shear-image order, as in shear-warp, the volume data set is resampled along slices parallel to a face of the volume. Unlike shear-warp, but like the texture-based methods, rays are cast through the centers of pixels of the image plane and sample points are at the intersections of rays with each slice. As a result, no post-warp step is required. Unlike texture methods, which realize shear and warp by transformations in a commodity graphics system, the shear-image ray casting methods use a new factorization that preserves memory and interpolation efficiency. In addition, a method is provided for accurately and efficiently embedding conventional polygon graphics and other objects into volumes. Both opaque and translucent polygons are supported.We also describe a method, included in shear-image order but applicable to other algorithms, for rendering anisotropic and sheared volume data sets directly with correct lighting.The shear-image order method has been implemented in the VolumeProTM 1000, a single chip real-time volume rendering engine capable of processing volume data at a pipeline rate of 109 samples per second. Figure 1 on the color page shows a shear-image order gallery of volumes rendered with different translucency, lighting, and some embedded geometry.

Bulk core in a 360/67 time-sharing system

In the fall of 1965, Carnegie Institute of Technology decided to install Large Capacity Core Storage (LCS) as the auxiliary storage device on its IBM 360/67 Time-Sharing computer system. The bulk core will be used as a swapping device, replacing the drums of conventional configurations, and as an extension of main core memory. The decision was motivated by an analysis which yielded the following results: • The effective rate at which the system can deliver pages to user tasks is increased to its theoretical limit with LCS, representing a significant improvement over drum performance. • The potential response time to users is decreased because LCS has no rotational delay. • Less main core is needed for effective system operation.

A real-time volume rendering architecture using an adaptive resampling scheme for parallel and perspective projections

The paper describes an object order real time volume rendering architecture using an adaptive resampling scheme to perform resampling operations in a unified parallel pipeline manner for both parallel and perspective projections. Unlike parallel projections, perspective projections require a variable resampling structure due to diverging perspective rays. In order to address this issue, we propose an adaptive pipelined convolution block for resampling operations using the level of resolution to keep the parallel pipeline structure regular. We also propose to use multi resolution datasets prepared for different levels of grid resolution to bound the convolution operations. The proposed convolution block is organized using a systolic array structure, which works well with a distributed skewed memory for conflict free accesses of voxels. We present the results of some experiments with our software simulators of the proposed architecture and discuss important technical issues.

Observations on the development of an operating system

The development of Pilot, an operating system for a personal computer, is reviewed, including a brief history and some of the problems and lessons encountered during this development. As part of understanding how Pilot and other operating systems come about, an hypothesis is presented that systems can be classified into five kinds according to the style and direction of their development, independent of their structure. A further hypothesis is presented that systems such as Pilot, and many others in widespread use, take about five to seven years to reach maturity, independent of the quality and quantity of the talent applied to their development. The pressures, constraints, and problems of producing Pilot are discussed in the context of these hypotheses.