About

Charles Reiss is an Assistant Professor on the General Faculty (Teaching Track) in the Computer Science Department at the University of Virginia. He serves as the department's study abroad advisor, providing guidance on the logistics of studying abroad for computer science majors. His teaching portfolio includes courses such as Computer Systems and Organization, Defense Against the Dark Arts, Computer Networks, Computer Architecture, and Operating Systems, reflecting a strong focus on systems and architecture education. Reiss has developed educational materials and software, including an educational hardware description language (HCLRS) used in computer organization courses and a web application for CPU cache exercises, supporting hands-on learning in computer systems. His scholarly contributions include work on hardware description languages for computer organization education and research on cloud computing heterogeneity and dynamics, recognized by a test of time award at SoCC 2021.

Research topics

• Computer Science
• Linguistics
• Philosophy
• Artificial Intelligence
• Speech recognition
• History
• Physics
• Cognitive science
• Mathematics
• Neuroscience
• Visual arts
• Arithmetic
• Cognitive psychology
• Art
• Psychology

Selected publications

• Votic Vowel Harmony in Substance-Free Logical Phonology

  Oxford University Press eBooks · 2024-10-22

  book-chapter

  Abstract This paper presents a novel account of Votic vowel harmony using components of substance-free Logical Phonology (LP). To appreciate the nature of LP, it is important not only to characterize it in positive terms, but also to highlight what it does not contain. Our LP account does not rely on notions such as contrast or markedness. Instead, we make use of formal properties like two kinds of vacuous rule application (via vacuous unification and unification failure) to derive a simple account of feature-filling patterns. Votic also provides an argument for substance-free phonology and against the notions of surface well-formedness and phonotactics playing a role in grammar. The non-functionalist, non-teleological nature of LP contrasts with output driven approaches to phonology. The analysis also resolves issues that were either unaddressed or unresolved in previous treatments.

  PublisherDOI

• Experiences with a Hardware Description Language for a CS-major's Computer Organization Course

  2023-10-18

  article1st authorCorresponding

  This article presents a novel hardware description language (HDL) and associated 4-week assignment sequence for a computer architecture course, with discussion of our experience developing and using these tools. At our institution, CS majors take a different computer architecture course than computer engineering majors. The CS majors' course aims to providestudents with an understanding of how nontrivial processors can be built out of simple hardware components. To leverage students' existing familiarity with programming languages, we wanted students to manipulate processor designs using a text-based hardware description language (HDL). We did not, however, want to devote instructional time to the low level complexities like clocking choices or arithmetic logic design. We developed an instructional hardware description language and associated assignments based on Bryant & O'Halleron's HCL (and designed to be compatible with their text) with some inspiration from Verilog. Unlike HCL, our HDL allows students with flexibility to build and simulate different processor organizations - for example, pipeline designs with different pipeline stages as well as non-pipelined designs - without the differences being hidden in the internal components of the simulator. By specializing for building a processor, our tooling prominently to students and our testing infrastructure how their simulated processors executed programs. Also, using simple enforcement of signal widths and avoiding floating or undefined values, our HDL design helped catch many students errors while still seeming to treat all values as bits. We also discuss our experience teaching a course using these tools to several hundred students a semester for the last eight years.We evaluate our experience through a review of student and instructor feedback, which suggest increased student and instructor satisfaction and that the HDL and assignments provide a solid basis for explaining later topics such as superscalar processors and processor-aware software optimization.

  PublisherDOI

• Conquer primal fear: Phonological features are innate and substance-free

  The Canadian Journal of Linguistics / La revue canadienne de linguistique · 2022 · 96 citations

  1st authorCorresponding
  • Linguistics
  • Cognitive science
  • Psychology

  Abstract We argue that the representational primes of the human phonological faculty, the so-called distinctive features, are innate and substance-free. Our arguments for the innateness of features are built on traditional and novel logical arguments, experimental evidence accumulating over recent decades, and somewhat detailed proposals about their neurobiological reality. As symbols in the brain, features are substance-free, that is, they are devoid of articulatory and acoustic content, or even any direct reference to such phenomena. This is consistent with our substance-free conception of phonological computation, an approach that eschews functionalist notions like markedness, ease of articulation, and so on. We also outline a neural model of the phonetics-phonology interface called Cognitive Phonetics, which transduces innate features to speech articulation and from speech acoustics. These extra-grammatical transduction procedures are also part of the human biological endowment, which leaves no room for language-specific phonetics in our theory of the externalization of language. We show how Cognitive Phonetics can account for traditionally recognized intersegmental coarticulation, as well as the previously unexplored intrasegmental coarticulation, strongly suggesting that the basic units of speech production are transduced features.

  PublisherOA PDFDOI

• NCC: Neighbor-aware Congestion Control based on Reinforcement Learning for Datacenter Networks

  2022-08-29 · 1 citations

  articleOpen access

  The challenges of low latency, high throughput datacenter networks create new traffic management problems that require new congestion control mechanisms. Generally, the proposals to solve this problem have focused either on refining existing window-based congestion control like in TCP or on introducing a central controller to make congestion control decisions. In this paper, we propose a third approach, where nodes share network information with their neighbors and apply this information to make local decisions that limit global congestion. In our implementation, the rate limiting decisions on one node are driven by the local agent that uses reinforcement learning to optimize a combination of overall latency, throughput and the shared information. To make this approach efficient, the local agents choose overall rate limits for each node, and then a separate process assigns the traffic of individual flows within these limits. We show that, in trace-driven real implementation, our method achieves better congestion avoidance than several end-to-end and centralized mechanisms in prior work.

  PublisherOA PDFDOI

• Towards a complete Logical Phonology model of intrasegmental changes

  Glossa a journal of general linguistics · 2021 · 81 citations

  1st authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Linguistics

  All changes to the internal structure of phonological segments arise from combinations of rules based on two set-theoretic operations: feature deletion by set subtraction and feature insertion by unification. Apparent cases of rules targeting underspecified segments reflect two kinds of vacuous rule application, one due to unification failure and the other due to vacuous unification. Despite this reduction of all segment-internal changes to two basic mechanisms we can account for a wide variety of patterns, including the reciprocal neutralization and apparent exceptional behavior seen in Hungarian voicing assimilation.

  PublisherOA PDFDOI

• Heterogeneity and Dynamicity of Clouds at Scale

  2021-11-01 · 7 citations

  article1st authorCorresponding

  Test of Time Award Talk for Heterogeneity and Dynamicity of Clouds at Scale: Google Trace Analysis, SoCC 2012.

  PublisherDOI

• Naturalism, Internalism, and Nativism: &amp;lt; What &amp;gt; The Legacy of<i>The Sound Pattern of English</i>&amp;lt; Should Be &amp;gt;

  2021-04-27

  other1st authorCorresponding

  Phonology is the study of abstract sound patterns in human language, as opposed to phonetics, which studies all aspects of speech, including articulation and acoustics. The phonology of each language consists of various computations. In Sound Pattern of English (SPE) the computations are called rules, and the phonology of a language is a complex function resulting from composing the rules in a particular order. Aside from internalism, naturalism and nativism are the most important notions of Chomsky's legacy in linguistics. SPE phonology explicitly adopts strict and consistent naturalism, internalism and nativism. The rightful legacy of SPE includes the naturalism, internalism and nativism found also in Chomsky's syntactic work. The SPE arguments given against building markedness into the formal theory are consistent with the idea of phonology as naturalistic inquiry, and these convincing arguments are only reinforced by the inconsistencies in markedness-based approaches.

  PublisherDOI

• Priority Union and Feature Logic in Phonology

  Linguistic Inquiry · 2020-08-06 · 2 citations

  article1st authorCorresponding

  Phonological rules built from a single operation, priority union, can model both feature-filling and feature-changing processes. The distinction is handled by specifying which argument of priority union is defeasible. Priority union should be considered as a candidate for inclusion in phonological Universal Grammar.

  PublisherDOI

• Geminates and vowel laxing in Quebec French

  Romance languages and linguistic theory · 2020 · 83 citations

  Senior authorCorresponding
  • Computer Science
  • Linguistics
  • Computer Science

  Abstract Laxing and harmony in Quebec French (QF) high vowels shows dialectal, register and perhaps even lexical variation. A recent proposal to handle some of the data ( Poliquin 2006 ) contains a radical innovation to phonological theory concerning long-distance segment interactions. We question the necessity of such an account by pointing out that recognition of geminate sonorants in QF can explain some puzzling forms without recourse to new devices. Our account is supported by phonetic considerations, as well as by recognizing that the alternative both under and overgenerates lax vowels in surface forms.

  PublisherDOI

• Improved Intermediate Data Management for MapReduce Frameworks

  2020-05-01 · 7 citations

  article

  MapReduce is a popular distributed framework for big data analysis. However, the current MapReduce framework is insufficiently efficient in handling intermediate data, which may cause bottlenecks in I/O operations, computation, and network bandwidth. Previous work addresses the I/O problem by aggregating map task outputs (i.e. intermediate data) for each single reduce task on one machine. Unfortunately, when there are a large number of reduce tasks, their concurrent requests for intermediate data generate a large amount of I/O operations. In this paper, we present APA (Aggregation, Partition, and Allocation), a new intermediate data management system for the MapReduce framework. APA aggregates the intermediate data from the map tasks in each rack to one file, and the file host pushes the needed intermediate data to each reduce task. Thus, it reduces the number of disk seeks involved in handling intermediate data within one job. Rather than evenly distributing the intermediate data among reduce tasks based on the keys as in current MapReduce, APA partitions the intermediate data to balance the execution latency of different reduce tasks. APA further decides where to allocate each reduce task to minimize the intermediate data transmission time between map tasks and reduce tasks. Through experiments on a real MapReduce Hadoop cluster using the HiBench benchmark suite, we show that APA improves the performance of the current Hadoop by 40%-50%.

  PublisherDOI

Frequent coauthors

• Mark Hale

  23 shared

• Randy H. Katz

  7 shared

• Madelyn Kissock

  5 shared

• David A. Patterson

  Google (United States)

  5 shared

• Ariel Rabkin

  Cloudera (United States)

  5 shared

• C. Robert

  Veolia (France)

  5 shared

• Veno Volenec

  Concordia University

  4 shared

• James S. Taylor

  GlaxoSmithKline (United Kingdom)

  4 shared

Labs

• Charles Reiss LabPI

  Not provided

Education

• Ph.D., Computer Systems

  Berkeley