Number Systems for Deep Neural Network Architectures: A Survey

Deep neural networks (DNNs) have become an enabling component for a myriad of artificial intelligence applications. DNNs have shown sometimes superior performance, even compared to humans, in cases such as self-driving, health applications, etc. Because of their computational complexity, deploying DNNs in resource-constrained devices still faces many challenges related to computing complexity, energy efficiency, latency, and cost. To this end, several research directions are being pursued by both academia and industry to accelerate and efficiently implement DNNs. One important direction is determining the appropriate data representation for the massive amount of data involved in DNN processing. Using conventional number systems has been found to be sub-optimal for DNNs. Alternatively, a great body of research focuses on exploring suitable number systems. This article aims to provide a comprehensive survey and discussion about alternative number systems for more efficient representations of DNN data. Various number systems (conventional/unconventional) exploited for DNNs are discussed. The impact of these number systems on the performance and hardware design of DNNs is considered. In addition, this paper highlights the challenges associated with each number system and various solutions that are proposed for addressing them. The reader will be able to understand the importance of an efficient number system for DNN, learn about the widely used number systems for DNN, understand the trade-offs between various number systems, and consider various design aspects that affect the impact of number systems on DNN performance. In addition, the recent trends and related research opportunities will be highlightedComment: 28 page

A Construction Kit for Efficient Low Power Neural Network Accelerator Designs

Implementing embedded neural network processing at the edge requires efficient hardware acceleration that couples high computational performance with low power consumption. Driven by the rapid evolution of network architectures and their algorithmic features, accelerator designs are constantly updated and improved. To evaluate and compare hardware design choices, designers can refer to a myriad of accelerator implementations in the literature. Surveys provide an overview of these works but are often limited to system-level and benchmark-specific performance metrics, making it difficult to quantitatively compare the individual effect of each utilized optimization technique. This complicates the evaluation of optimizations for new accelerator designs, slowing-down the research progress. This work provides a survey of neural network accelerator optimization approaches that have been used in recent works and reports their individual effects on edge processing performance. It presents the list of optimizations and their quantitative effects as a construction kit, allowing to assess the design choices for each building block separately. Reported optimizations range from up to 10'000x memory savings to 33x energy reductions, providing chip designers an overview of design choices for implementing efficient low power neural network accelerators

Fast, area-efficient 32-bit LNS for computer arithmetic operations

PhD ThesisThe logarithmic number system has been proposed as an alternative to floating-point. Multiplication, division and square-root operations are accomplished with fixedpoint arithmetic, but addition and subtraction are considerably more challenging. Recent work has demonstrated that these operations too can be done with similar speed and accuracy to their floating-point equivalents, but the necessary circuitry is complex. In particular, it is dominated by the need for large lookup tables for the storage of a non-linear function. This thesis describes the architectures required to implement a newly design approach for producing fast and area-efficient 32-bit LNS arithmetic unit. The designs are structured based on two different algorithms. At first, a new cotransformation procedure is introduced in the singularity region whilst performing subtractions in which the technique capable to generate less total storage than the cotransformation method in the previous LNS architecture. Secondly, improvement to an existing interpolation process is proposed, that also reduce the total tables to an extent that allows their easy synthesis in logic. Consequently, the total delays in the system can be significantly reduced. According to the comparison analysis with previous best LNS design and floating-point units, it is shown that the new LNS architecture capable to offer significantly better in speed while sustaining its accuracy within floating-point limit. In addition, its implementation is more economical than previous best LNS system and almost equivalent with existing floating-point arithmetic unit.University Malaysia Perlis: Ministry of Higher Education, Malaysia

Application-Specific Number Representation

Reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), enable application- specific number representations. Well-known number formats include fixed-point, floating- point, logarithmic number system (LNS), and residue number system (RNS). Such different number representations lead to different arithmetic designs and error behaviours, thus produc- ing implementations with different performance, accuracy, and cost. To investigate the design options in number representations, the first part of this thesis presents a platform that enables automated exploration of the number representation design space. The second part of the thesis shows case studies that optimise the designs for area, latency or throughput from the perspective of number representations. Automated design space exploration in the first part addresses the following two major issues: ² Automation requires arithmetic unit generation. This thesis provides optimised arithmetic library generators for logarithmic and residue arithmetic units, which support a wide range of bit widths and achieve significant improvement over previous designs. ² Generation of arithmetic units requires specifying the bit widths for each variable. This thesis describes an automatic bit-width optimisation tool called R-Tool, which combines dynamic and static analysis methods, and supports different number systems (fixed-point, floating-point, and LNS numbers). Putting it all together, the second part explores the effects of application-specific number representation on practical benchmarks, such as radiative Monte Carlo simulation, and seismic imaging computations. Experimental results show that customising the number representations brings benefits to hardware implementations: by selecting a more appropriate number format, we can reduce the area cost by up to 73.5% and improve the throughput by 14.2% to 34.1%; by performing the bit-width optimisation, we can further reduce the area cost by 9.7% to 17.3%. On the performance side, hardware implementations with customised number formats achieve 5 to potentially over 40 times speedup over software implementations

Identification and functional characterization of the human and murine OSTL gene, which encodes a RING-DRIL-RING domain protein possibly involved in B cell differentiation and leukemogenesis

The OSTL gene is localized at the band q23 in the chromosome 6. Its localization corresponds to a translocation breakpoint between chromosomes 6 and 12, the t(6;12)(q23;p13), that was characterized in our group in an acute lymphoblastic leukemia cell line. This translocation involves the ETV6 (translocation ETs leukemia) gene localized in chromosome 12 with the STL (six twelve leukemia gene) gene localized in chromosome 6. The STL gene shares the first exon with a novel gene, that we named OSTL (opposite STL), but they are transcribed in opposite directions. Since the fusion gene ETV6/STL encodes only for a very small protein which lacks any known functional domain, we speculate that the main leukemogenic effect of this translocation is the deregulation of OSTL. OSTL has a RING-Finger motif that is highly conserved between species and has a significant homology with other genes in human as well as C. elegans, D. melanogaster, and S. cerevisiae. OSTL showed a very specific expression pattern during the mouse embryogenesis. The aim of this project was the functional characterization of OSTL, with special emphasis in normal hematopoiesis and leukemogenesis. Therefore we have sequenced the whole human and mouse OSTL cDNA by using OSTL cDNA clones from the RZPD (“Resource Zentrum Primäre Datenbank”) in Berlin. These sequences encode for a 307 (mouse) and a 275 (human) amino acids length protein. The protein length differences between human and mouse are explained because of the existence of alternative spliced exons. The homology between human and mouse sequence is 99% at the protein level. The expression of GFP-OSTL fusion protein in mouse fibroblast cell line enable us to observe the subcellular localization of OSTL protein. GFP-OSTL is localized mainly in the cytoplasm, showing small spots, probably in the mitochondrial region. In a mouse multiple tissue Northern blot, we could show that OSTL is expressed in testis, ovary and liver. In an human multiple tissue Northern, OSTL expression was observed in skeletal muscle, testis, ovary, heart, placenta, pancreas and prostate. Northern blotting with different human cell lines revealed expression of OSTL in three EBV (Epstein Barr Virus) transformed lymphoblastoid cell lines (LCL B, LCL D, and LCL R) and in one NHL (Non-Hodgkin Lymphoma) cell line (Karpas 422). In Reverse Transcriptase PCR experiments using B cell in different maturation stages, the expression of OSTL was observed in naive, memory B and plasma cells, and in leukemic patient samples, expression was observed in several AML and ALL cDNAs. Whole mount in situ hybridization experiments were performed to investigate the temporo-spatial expression pattern of OSTL during mouse embryogenesis. There was distinct expression of Ostl in the somites (myotome), first and second branchial arches, optic and otic vesicles, in the hair follicles of the vibrissae, and limb buds in mouse embryos of embryonal days 9.5 to 14.5. This expression pattern suggests an important role for Ostl in the early development of these structures. Aiming to find protein interaction partners of OSTL, we performed a Yeast Two Hybrid assay using a Hela cDNA library. Among others we found interaction of OSTL with the antiapoptotic protein, HAX-1 (HS1-associated protein X-1), that is involved in the regulation of B-cell signal transduction, and interaction with the pro-apoptotic protein, SIVA. SIVA was originally identified as an interaction partner of CD27 (TNFRSF7), a member of the TNF-receptor superfamily, which is expressed in B cells. These interactions were confirmed by in vitro (cotransformation in yeast, CoIP) and in vivo (colocalization of these proteins in mammalian cells and CoIP) assays. Overexpression of Ostl in primary mouse hematopoietic cells followed by injection of the cells into lethally irradiated mice resulted in a T-Acute-Lymphoblastic-Leukemia (T-ALL) phenotype. In summary, our experiments could demonstrate that OSTL is important in B cell development and signaling and deregulation of this gene can contribute to the development of hematologic malignancies

Arithmetic with the Two-Dimensional Logarithmic Number System (2DLNS)

The ever increasing demand for low power DSP applications has directed researchers to contemplate a variety of potential approaches in different contexts. Since DSP algorithms heavily rely on multiplication, there are growing demands for more efficient multiplication structures. In this regard, using some alternative number systems, which inherently are capable of reducing the hardware complexity, have been studied. The Multi-Dimensional Logarithmic Number System (MDLNS), a multi-digit and multi-base extension to the Logarithmic Number System (LNS), is considered as an alternative to the traditional binary representation for selected applications. The MDLNS provides a reduction in the size of the number representation with a non-linear mapping and promises a lower cost realization of arithmetic operations with a reduced hardware complexity. In addition, using the recursive multiplication technique, which refers to the published multiplication algorithm that uses smaller multipliers to implement a larger operation, reduces the size of operands and corresponding partial additions. As part of this research, 2DLNS-based multiplication architectures with two different levels of recursion are presented. These architectures combine some of the exibility of software with the high performance of hardware by implementing the recursive multiplication schemes on a 2DLNS processing structure. These implementations demonstrate the efciency of 2DLNS in DSP applications and show outvistanding results in terms of operation delay and dynamic power consumption. We also demonstrate the application of recursive 2DLNS multipliers to reconfigurable multiplication architectures. These architectures are able to perform single and double precision multiplication, as well as fault tolerant and dual throughput single precision operations. Modern DSP processors, such as those used in hand-held devices, may find considerable benefit from these high-performance, low-power, and high-speed recongurable architectures. In the final part of this research work, recursive 2DLNS multiplication architectures have been applied to a FIR lter structure. These implementations show considerable improvement to their binary counterparts in terms of VLSI area and power consumption

Comparison of logarithmic and floating-point number systems implemented on Xilinx Virtex-II field-programmable gate arrays

The aim of this thesis is to compare the implementation of parameterisable LNS (logarithmic number system) and floating-point high dynamic range number systems on FPGA. The Virtex/Virtex-II range of FPGAs from Xilinx, which are the most popular FPGA technology, are used to implement the designs. The study focuses on using the low level primitives of the technology in an efficient way and so initially the design issues in implementing fixed-point operators are considered. The four basic operations of addition, multiplication, division and square root are considered. Carry- free adders, ripple-carry adders, parallel multipliers and digit recurrence division and square root are discussed. The floating-point operators use the word format and exceptions as described by the IEEE std-754. A dual-path adder implementation is described in detail, as are floating-point multiplier, divider and square root components. Results and comparisons with other works are given. The efficient implementation of function evaluation methods is considered next. An overview of current FPGA methods is given and a new piecewise polynomial implementation using the Taylor series is presented and compared with other designs in the literature. In the next section the LNS word format, accuracy and exceptions are described and two new LNS addition/subtraction function approximations are described. The algorithms for performing multiplication, division and powering in the LNS domain are also described and are compared with other designs in the open literature. Parameterisable conversion algorithms to convert to/from the fixed-point domain from/to the LNS and floating-point domain are described and implementation results given. In the next chapter MATLAB bit-true software models are given that have the exact functionality as the hardware models. The interfaces of the models are given and a serial communication system to perform low speed system tests is described. A comparison of the LNS and floating-point number systems in terms of area and delay is given. Different functions implemented in LNS and floating-point arithmetic are also compared and conclusions are drawn. The results show that when the LNS is implemented with a 6-bit or less characteristic it is superior to floating-point. However, for larger characteristic lengths the floating-point system is more efficient due to the delay and exponential area increase of the LNS addition operator. The LNS is beneficial for larger characteristics than 6-bits only for specialist applications that require a high portion of division, multiplication, square root, powering operations and few additions

Novel Architectures for Offloading and Accelerating Computations in Artificial Intelligence and Big Data

Due to the end of Moore's Law and Dennard Scaling, performance gains in general-purpose architectures have significantly slowed in recent years. While raising the number of cores has been a viable approach for further performance increases, Amdahl's Law and its implications on parallelization also limit further performance gains. Consequently, research has shifted towards different approaches, including domain-specific custom architectures tailored to specific workloads. This has led to a new golden age for computer architecture, as noted in the Turing Award Lecture by Hennessy and Patterson, which has spawned several new architectures and architectural advances specifically targeted at highly current workloads, including Machine Learning. This thesis introduces a hierarchy of architectural improvements ranging from minor incremental changes, such as High-Bandwidth Memory, to more complex architectural extensions that offload workloads from the general-purpose CPU towards more specialized accelerators. Finally, we introduce novel architectural paradigms, namely Near-Data or In-Network Processing, as the most complex architectural improvements. This cumulative dissertation then investigates several architectural improvements to accelerate Sum-Product Networks, a novel Machine Learning approach from the class of Probabilistic Graphical Models. Furthermore, we use these improvements as case studies to discuss the impact of novel architectures, showing that minor and major architectural changes can significantly increase performance in Machine Learning applications. In addition, this thesis presents recent works on Near-Data Processing, which introduces Smart Storage Devices as a novel architectural paradigm that is especially interesting in the context of Big Data. We discuss how Near-Data Processing can be applied to improve performance in different database settings by offloading database operations to smart storage devices. Offloading data-reductive operations, such as selections, reduces the amount of data transferred, thus improving performance and alleviating bandwidth-related bottlenecks. Using Near-Data Processing as a use-case, we also discuss how Machine Learning approaches, like Sum-Product Networks, can improve novel architectures. Specifically, we introduce an approach for offloading Cardinality Estimation using Sum-Product Networks that could enable more intelligent decision-making in smart storage devices. Overall, we show that Machine Learning can benefit from developing novel architectures while also showing that Machine Learning can be applied to improve the applications of novel architectures

Untersuchung TRPC-modulierender Gestagene und Proteine

In the first part of this study, we have identified the two steroid hormones progesterone and norgestimate as novel TRPC channel blockers. Both substances blocked TRPC-mediated Ca2+ influx with micromolar activities in fluorometric measurements. TRPC channel inhibition did not seem to be a general steroid effect since another progestin, the norgestimate metabolite levonorgestrel, was not effective. Norgestimate was 4- to 5-fold more active on the TRPC3/6/7 subfamily compared to TRPC4/5, whereas progesterone was similarly potent. This selectivity of norgestimate was confirmed by patch clamp recordings. As norgestimate blocked channels directly gated by DAG with a fast kinetic, we assume the compound acts on the channel protein itself. This view was further substantiated by the lack of effects on IP3R-mediated Ca2+ release from the endoplasmic reticulum, which is activated in parallel with TRPCs by Gq/11-coupled receptor stimulation. Norgestimate did not only block ectopically expressed TRPC channels but also native, TRPC-mediated currents in rat aortic smooth muscle cells with similar activity. The usefulness of norgestimate as a tool compound for the investigation of physiological TRPC functions was tested in isolated vessel rings. Consistent with TRPC6 being an essential component of the alpha-1-adrenoceptor-activated cation channel, we demonstrated a direct vasorelaxant, endothelium-independent effect of norgestimate on rat aortic rings precontracted with phenylephrine. Thus, our results provide further experimental support for a role of TRPC6 in alpha-1-adrenergic vessel constriction. In the second part of this study, we screened a human aorta cDNA-library for novel TRPC4-interacting proteins with a modified yeast two-hybrid (Y2H) system in which the TRPC4-C-terminus was expressed as tetrameric bait protein, thereby mimicking the native channel conformation. Of the eleven interacting proteins found SESTD1 was chosen for further analyses since it contains a phospholipid-binding Sec14p-like domain and thus could be involved in regulation of TRPC channels by phospholipids. After the biochemical validation of the found interaction, the first spectrin domain of SESTD1 was then identified to interact with the CIRB domain of TRPC4 in directed Y2H tests. SESTD1 also co-immunoprecipitated with the closely related TRPC5 protein in which the SESTD1-binding domain is highly conserved. Independent of the CIRB site, co-immunoprecipitation with TRPC6 and the distantly related TRPM8 channel was observed indicating the existence of other sites in these channel proteins that mediate interaction with SESTD1. Analysis of SESTD1 gene expression in human tissues showed that its transcripts are ubiquitously expressed and tissues with significant coexpression with TRPC4 and -5 were identified. We have generated two polyclonal antisera directed against SESTD1 that consistently detected SESTD1 protein in brain, aorta, heart, and in smooth muscle and endothelial cells. The functional consequences of the found interaction were investigated by examination of the TRPC5-mediated Ca2+ influx in a clonal HM1 cell line stably expressing the channel. Since SESTD1 overexpression had no detectable effects on TRPC5-mediated Ca2+ influx, most likely due to expression of endogenous SESTD1, we knocked-down the native protein with specific siRNA. This procedure reduced TRPC5-mediated Ca2+ influx following receptor stimulation by 50%. Parallel biotinylation experiments did not reveal any differences in cell surface expressed TRPC5-protein, suggesting that reduction of TRPC5 activity resulted from a loss of a direct SESTD1 effect on the channel. In addition, in immunofluorescence experiments we observed that reduced SESTD1 protein levels resulted in a redistribution of the multifunctional protein ß-catenin from the plasma membrane to the cytosol. This result may point to an involvement of SESTD1 in formation and maintenance of adherens junctions. SESTD1 contains a phospholipid-binding Sec14p-like domain and we were the first to demonstrate its Ca2+-dependent binding to phosphatidic acid and all physiological phosphatidylinositol mono- and bisphosphates in vitro. The physiological function of this binding activity is not known at present, but it could play a role in regulation of associated TRPC channels. TRPC4 and -5 channels are activated by phospholipid hydrolysis and also bind phospholipids directly. The identification of SESTD1 as novel TRPC-interacting protein could thus be an important step forward in the investigation and better comprehension of the complex molecular mechanisms of TRP channel regulation by lipids.Im ersten Teil der vorliegenden Arbeit wurden zwei Gestagene, Progesteron und Norgestimat, als neue TRPC-Kanalinhibitoren identifiziert. Sie hemmten den TRPC-vermittelten Ca2+-Einstrom in fluorometrischen Messungen im mikromolaren Konzentrationsbereich. Ein Metabolit des Norgestimats, das Levonorgestrel, war hingegen nicht wirksam. Diese unterschiedliche Wirkung der strukturell nahe verwandten Substanzen schließt eine unspezifische Hemmung von TRPCs durch diese Steroide aus. Norgestimat hemmte die Vertreter der TRPC3/6/7-Unterfamilie vier- bis fünfmal stärker als TRPC4/5 während die Wirkung von Progesteron auf beide Unterfamilien vergleichbar war. Patch Clamp-Untersuchungen bestätigten die Selektivität von Norgestimat. Da Norgestimat Kanäle, die direkt durch DAG aktiviert werden, mit einer schnellen Kinetik blockte, nehmen wir an, dass es die Kanalproteine direkt hemmt. Dafür spricht auch, dass es keinen Effekt auf die IP3R-vermittelte Ca2+-Freisetzung aus dem endoplasmatischen Retikulum hatte, die parallel zu TRPCs durch Gq/11-gekoppelte Rezeptorstimulation aktiviert wird. Norgestimat hemmte heterolog exprimierte Kanäle und native, TRPC-vermittelte Ströme in glatten Gefäßmuskelzellen aus Rattenaorten mit vergleichbarer Aktivität. Die Eignung von Norgestimat als pharmakologisches Werkzeug zur Untersuchung physiologischer TRPC-Funktionen testeten wir in isolierten Gefäßringen. An vorkontrahierten Aortenringen aus der Ratte konnte nach Gabe von Norgestimat eine endothel-unabhängige Relaxation beobachtet werden. In Übereinstimmung mit bekannten Literaturdaten legt auch dieses Ergebnis nahe, dass TRPC6-Kanäle an der Regulation des Gefäßtonus beteiligt sind. Im zweiten Teil der Arbeit wurde eine cDNS-Bibliothek aus humanen Aorten mit Hilfe eines modifizierten Hefe Zwei-Hybrid Systems durchmustert. Als Köderprotein diente der C-Terminus des TRPC4-Kanalproteins, der als tetrameres Fusionsprotein, d.h. in seiner nativen Konformation, vorlag. Elf Proteine wurden isoliert, von denen das SESTD1-Protein für weitergehende Untersuchungen ausgewählt wurde, weil es eine phospholipidbindende Sec14p-Domäne besitzt. Damit könnte es an der TRPC-Kanalregulation durch Phospholipide beteiligt sein. Seine Interaktion mit TRPC4 wurde mit proteinbiochemischen Methoden bestätigt. In gerichteten Interaktionsstudien in Hefezellen wurde die erste Spektrindomäne von SESTD1 als Bindungspartner der CIRB-Domäne von TRPC4 identifiziert. SESTD1 band auch das nahe verwandte TRPC5-Protein, in dem die SESTD1-Interaktionssequenz hoch konserviert ist. Die CIRB-unabhängige Koimmunopräzipitation von SESTD1 mit TRPC6 und dem entfernter verwandten TRPM8-Kanalprotein weist jedoch darauf hin, dass diese TRP-Kanäle noch weitere SESTD1-Bindungsstellen besitzen müssen. Die Analyse der SESTD1-Transkriptexpression in verschiedenen humanen Geweben zeigte, dass SESTD1 ubiquitär und damit überlappend mit TRPC4 bzw. -5 exprimiert wird. Für den Nachweis des SESTD1-Proteins wurden zwei polyklonale Antikörper hergestellt, mit denen es in Übereinstimmung mit diesen Daten in Gehirn, Herz, Aorta, Glattmuskel- und Endothelzellen nachgewiesen werden konnte. Zur funktionellen Charakterisierung der gefundenen Interaktion wurden mögliche Wirkungen von SESTD1 auf den TRPC5-vermittelten Ca2+-Einstrom exemplarisch in einer klonalen HM1-Zelllinie untersucht, die den Kanal stabil exprimiert. Die Überexpression von SESTD1 in dieser Zelllinie hatte keinen signifikanten Effekt auf den TRPC5-vermittelten Ca2+-Einstrom. Deshalb wurde die Menge des endogenen SESTD1-Proteins mittels spezifischer siRNA stark reduziert, wodurch auch der TRPC5-vermittelte Ca2+-Einstrom nach Rezeptorstimulation um etwa die Hälfte verringert wurde. Biotinylierungsstudien zeigten, dass die Menge des TRPC5-Proteins an der Plasmamembran nicht verändert war, was wiederum einen direkten Einfluss von SESTD1 auf die Kanalaktivität nahelegt. Immunfluoreszenzstudien zeigten außerdem, dass die siRNA-vermittelte Reduzierung der SESTD1-Proteinexpression zu einer Umverteilung des multifunktionellen ß-Catenin-Proteins von der Plasmamembran in das Zytosol führte. SESTD1 ist also möglicherweise an der Bildung und/oder Aufrechterhaltung von Zell-Zell-Kontakten beteiligt. SESTD1 besitzt eine phospholipidbindende Sec14p-Domäne und wir zeigen erstmalig, dass es Phosphatidylsäure und alle physiologisch vorkommenden Phosphatidylinositolmono- und -diphosphate in vitro bindet und diese Bindung Ca2+-abhängig moduliert wird. Die physiologische Relevanz dieser Bindung ist bisher nicht bekannt. Phospholipide sind in komplexer Weise an der Regulation von TRPC4/5 beteiligt. Sie stellen das Substrat für die zur Kanalaktivierung essentiellen Hydrolysefunktionen von PLC dar und binden darüber hinaus direkt an die Kanalproteine. Die Identifizierung von SESTD1 als TRPC-interagierendes Protein könnte ein wichtiger Schritt zur mechanistischen Aufklärung der Kanal-Lipid-Wechselwirkung sowie ihrer funktionellen Konsequenzen sein

Studies on the Agrobacterium Mediated Transformation of Potato (Solanum Tuberosum L.) and Tobacco (Nicotiana Tabacum L.) With Antibacterial and High Essential Amino Acids Encoding Genes.

Tuber disks from four cultivars of Solanum tuberosum L. were cultured on a Murashige and Skoog medium supplemented with B5 vitamins, 3.0% sucrose, 0.7% phytagar and ratios of indole-3-actyl-aspartic acid (IAAa) and zeatin riboside (ZR). No shoots were regenerated from Red LaSoda. Russet Burbank, Desiree, and LaBelle tuber disks produced shoots over a range of IAAa and ZR ratios. The greatest number of shoots was regenerated from Russet Burbank at 1 $\mu$M IAAa and 8 $\mu$M ZR. Different potato cultivars were also tested for their responses to Agrobacterium infections. Growth stage of the bacterial cultures and exposure duration of tuber disks to bacteria did not have a significant effect. However, significant differences among the cultivars in their responses to infection from A. rhizogenes and A. tumefaciens strains were observed. When effects of lytic peptides SB-37 and Shiva-1 on growth of plant pathogenic fungi were tested, a complete inhibition was observed at 10\sp{-3} M, whereas, a mild stimulation of growth was noted at 10\sp{-5} M. The effect of SB-37 on tobacco-cell suspensions was also tested. Cell growth was inhibited at 10\sp{-3} M and somewhat arrested at 10\sp{-4} M. At 10\sp{-6} M and 10\sp{-7} M SB-37 growth of the cells was stimulated. Leaf disks from transgenic and nontransgenic tobacco (Nicotiana tabacum L.) plants were exposed to a disarmed A. tumefaciens containing genes in a binary vector arrangement with one set of constructs for antibacterial (lytic) peptides and with another set of constructs for high essential amino acids (HEAA) II. Positive beta-glucuronidase (GUS) activity indicated that transformation had been obtained for both transgenic and nontransgenic plants. Although GUS positive plants were obtained with A. tumefaciens carrying HEAA II, transgenic plants were not exposed to this vector. Kanamycin resistant shoots regenerated from Russet Burbank tuber disks infected with binary A. tumefaciens vectors carrying antibacterial and HEAA II genes were also obtained